Indicator Values Research Articles

Path Updating of the Legal Ontology Model for Personal Information Protection in the Age of Big Data

Abstract This paper proposes a legal ontology model for personal information protection to extract structured information on the high-frequency elements of common privacy leakage and data security cases as key information of judicial documents. The prediction model of relevant sentences based on the CART decision tree is used to predict the outcome of the defendant’s sentence. The application scenarios of the legal ontology model of personal information protection in judicial guarantee are explored to guarantee the fairness of adjudication of personal information protection cases in terms of reliability of legal counseling, accuracy of sentencing assistance, and categorization of cases. The results show that 113 sample cases were retrieved by keyword search, excluding duplicate cases, with Beijing having the highest number of 42. With the development of the big data era, there has been a significant increase in personal information protection cases after 2019. The legal ontology model constructed in this paper has only 56 instances of classification error, the Macro-F1-Score and Micro-F1-Score indicator values are above 70%, and the utility values of personal information protection-related cases are all higher than 0.5. Therefore, the legal ontology model for personal information protection constructed in this paper is accurate in classification and sentencing prediction, with high reliability, and realizes the path of the big data era.

Future Prediction of Close Contacts in IoT-based Contact Tracing System using a New Real-Life Dataset.

Contact tracing is an effective method for mitigating the infectious diseases spread and it played a crucial role in reducing COVID-19 outbreak. Since the pandemic, there has been an increased concern regarding people's health in hospital and office settings, as these limited air exchange spaces provide a conductive medium for virus spread. Various technologies were used to recognize close contacts autonomously, in addition, multiple machine learning attempts were carried out to determine proximity in contact tracing. This study, however, proposes a unique concept in contact tracing: forecasting future close contact prior to occurrence in order to regulate and control it rather than tracking past occurrences. For our research, we constructed a completely new real-life dataset that was collected during the pandemic in a hospital infectious ward (Alfred Hospital, Melbourne, Australia) utilizing a Bluetooth Low Energy (BLE) Internet of Things (IoT) system. Our prediction technique considers two types of environments: single transceiver environments and multiple transceivers settings, these transceivers record the nearby tags' BLE received signal strength indicator (RSSI) values. The system employs mathematical models and supervised machine learning (ML) algorithms to solve regression and classification problems for workers' pattern recognition within the environment. The output is compared using different metrics, such as efficiency, which reached more than 80%, root mean square errors and mean absolute errors which were as low as 2.4 and 1.2 respectively in some models.

Nutrient‐demanding and thermophilous plants dominate urban forest‐edge vegetation across temperate Europe

AbstractQuestionsForests are highly fragmented across the globe. For urban forests in particular, fragmentation increases the exposure to local warming caused by the urban heat island (UHI) effect. We here aim to quantify edge effects on herbaceous understorey vegetation in urban forests, and test whether these effects interact with forest structural complexity.LocationWe set up a pan‐European study at the continental scale including six urban forests in Zurich, Paris, Katowice, Brussels, Bremen, and Stockholm.MethodsWe recorded understorey plant communities from the edge towards the interior of urban forests. Within each urban forest, we studied edge‐to‐interior gradients in paired stands with differing forest structural complexity. Community composition was analysed based on species specialism, life form, light, nutrient, acidity and disturbance indicator values and species' thermal niches.ResultsWe found that herbaceous communities at urban forest edges supported more generalists and forbs but fewer ferns than in forests' interiors. A buffered summer microclimate proved crucial for the presence of fern species. The edge communities contained more thermophilous, disturbance‐tolerant, nutrient‐demanding and basiphilous plant species, a pattern strongly confirmed by corresponding edge‐to‐interior gradients in microclimate, soil and light conditions in the understorey. Additionally, plots with a lower canopy cover and higher light availability supported higher numbers of both generalists and forest specialists. Even though no significant interactions were found between the edge distance and forest structural complexity, opposing additive effects indicated that a dense canopy can be used to buffer negative edge effects.ConclusionThe urban environment poses a multifaceted filter on understorey plant communities which contributes to significant differences in community composition between urban forest edges and interiors. For urban biodiversity conservation and the buffering of edge effects, it will be key to maintain dense canopies near urban forest edges.

The phytocoenology, distribution, and habitat preferences of the species Aldrovanda vesiculosa (Droseraceae) in Romania

Aldrovanda vesiculosa is an endangered aquatic species in Romania which grows in shallow waters where competition with other aquatic species is limited or absent. A comprehensive overview of the species? distribution and habitat preferences in Romania is currently lacking. In this context, this study aimed to update the distribution and habitat preferences of the species. Localities from Dobrogea, Oltenia, Muntenia, Transylvania, and Cri?ana represented the study areas. For the vegetation classification, 71 releves with A. vesiculosa were analysed. The size of the sample areas ranged from 4 m2 to 25 m2. Vegetation syntaxonomic assignment was performed by agglomerative hierarchical clustering. The optimal number of clusters was chosen using the corrected Rand and Silhouette indices. Diagnostic species were identified for each cluster based on the indicator value index (IndVal). The study results showed that the dominant majority of the previous populations of A. vesiculosa (89%) were no longer identified from Romania in the 2008?2021 period. Recently (2021?2023), they were found only in six localities in the Dobrogea, Transylvania, and Oltenia regions. The causes of the disappearance of the species are eutrophication and the lowering of the water level. From a phytocoenological point of view, 11 plant communities were identified where A. vesiculosa is found. According to the EUNIS classification, this species inhabits wetlands (Q) and inland surface waters (C). In conclusion, translocation is suggested as the primary conservation measure for protecting the species.

Research on the Integration Mode of Teaching Chinese Cultural Elements and English Translation Courses Based on the Integration Model

Abstract How to integrate Chinese cultural elements with English translation courses has been a major topic of discussion within English teaching. For this, this paper proposes to integrate traditional Chinese cultural elements into English translation courses, combining the entropy weighting method and the gray correlation analysis method to calculate the degree of integration and influencing factors of the two. It firstly eliminates the incomparability caused by different outlines and the positive and negative directions of the indicators through the dimensionless processing of the indicator values, and secondly uses the entropy weighting method to calculate the objective weights of the indicators, and applies TOPSIS to make a comprehensive evaluation. To assess the integration of Chinese cultural elements and English translation course teaching at this school, use gray correlation analysis. The practical application of designing English translation test papers with Chinese cultural elements and integrating traditional Chinese cultural elements into the teaching of English courses was carried out at a university. The correlation between article translation and the total score is the largest (0.728), and the correlation of basic translation ability is 0.658. The ones that have an impact on the translation ability of Chinese traditional elements are, in descending order, basic reading (0.8175), listening to English (0.7951), comprehensive ability (0.7422), and English writing (0.6384).

Identification of cachexia in lung cancer patients with an ensemble learning approach.

Nutritional intervention prior to the occurrence of cachexia will significantly improve the survival rate of lung cancer patients. This study aimed to establish an ensemble learning model based on anthropometry and blood indicators without information on body weight loss to identify the risk factors of cachexia for early administration of nutritional support and for preventing the occurrence of cachexia in lung cancer patients. This multicenter study included 4,712 lung cancer patients. The least absolute shrinkage and selection operator (LASSO) method was used to obtain the key indexes. The characteristics excluded weight loss information, and the study data were randomly divided into a training set (70%) and a test set (30%). The training set was used to select the optimal model among 18 models and verify the model performance. A total of 18 machine learning models were evaluated to predict the occurrence of cachexia, and their performance was determined using area under the curve (AUC), accuracy, precision, recall, F1 score, and Matthews correlation coefficient (MCC). Among 4,712 patients, 1,392 (29.5%) patients were diagnosed with cachexia based on the framework of Fearon et al. A 17-variable gradient boosting classifier (GBC) model including body mass index (BMI), feeding situation, tumor stage, neutrophil-to-lymphocyte ratio (NLR), and some gastrointestinal symptoms was selected among the 18 machine learning models. The GBC model showed good performance in predicting cachexia in the training set (AUC = 0.854, accuracy = 0.819, precision = 0.771, recall = 0.574, F1 score = 0.658, MCC = 0.549, and kappa = 0.538). The abovementioned indicator values were also confirmed in the test set (AUC = 0.859, accuracy = 0.818, precision = 0.801, recall = 0.550, F1 score = 0.652, and MCC = 0.552, and kappa = 0.535). The learning curve, decision boundary, precision recall (PR) curve, the receiver operating curve (ROC), the classification report, and the confusion matrix in the test sets demonstrated good performance. The feature importance diagram showed the contribution of each feature to the model. The GBC model established in this study could facilitate the identification of cancer cachexia in lung cancer patients without weight loss information, which would guide early implementation of nutritional interventions to decrease the occurrence of cachexia and improve the overall survival (OS).

ОЦЕНКА ИСПОЛЬЗОВАНИЯ НАСЕЛЕНИЕМ СЕТИ ИНТЕРНЕТ ДЛЯ ЗАКАЗОВ ТОВАРОВ И/ИЛИ УСЛУГ (ПО МАТЕРИАЛАМ ВЫБОРОЧНЫХ ОБСЛЕДОВАНИЙ): ПРОБЛЕМЫ ПОВЫШЕНИЯ КАЧЕСТВА ЗНАЧЕНИЙ ПОКАЗАТЕЛЕЙ

In this article, the authors consider the results of surveys of the population of the Russian Federation for the period from 2018 to 2021. The analysis of the use of the Internet by the population for ordering goods and/or services (based on the materials of sample surveys) in the context of age, type of goods/services, payment methods and reasons for not using the Internet to order goods/services was performed. The main problems of improving the quality of indicator values are identified, and the main directions for solving these problems are proposed.

Pelatihan Pembuatan Modul Ajar Inovatif Sesuai Tuntutan Kurikulum Merdeka di Desa Serdang

This community service activity aims to train teachers in Serdang village, Beringin sub-district in designing innovative teaching modules according to the demands of the independent curriculum, which will be implemented in October-November 2023 with partners as the principal of SD Negeri 101917 and the head of Serdang village, Beringin sub-district, Deli district. Serdang. The location of the activity was held at the Serdang Village meeting office with a capacity of 80 participants. The results of the activities obtained from observations show that the overall achievement of the goals that have been set appears to be in the "very good" category because the indicator value (I) = 4.603 ≥ which means that the activity implementation process has been carried out well. From the evaluation results of PkM activities, it can also be seen that there is a decrease from the evaluation results during PkM activities to the evaluation results after PkM activities, namely from an average of 90.86% down to an average of 89.79%. From the results of the total average of medium completion and high completion, it shows that the motivation of training participants in developing innovative learning processes, designing innovative learning programs according to the demands of the independent curriculum, innovating teaching modules based on innovative learning models, and becoming professional teachers according to the demands of the independent curriculum has increased.

Exploration of the Potential Geosite of Ijen Geopark Bondowoso Region as an Educational Tourism

Geosite is one of the Ijen Geopark geosites in the Bondowoso region which has an initial design as a tourist destination which in its management only implements elements of tourism. Then after the Ijen Geopark was designated as a National Geopark and proposed to become part of the UNESCO Global Geopark (UGG), the status of the Wurung Crater, which was originally a destination, changed to a Geological Heritage Site (Geosite). This status change in its adjustment in the field with the concept of educational tourism is still not maximized. Geosite management needs to implement elements of tourism, science and education. The management concept is considered in accordance with the concept of educational tourism which includes tourism and educational activities. So the purpose of this research is to find out what potential the Wurung Crater geosite has so that it can meet the educational tourism indicators which consist of tutorial learning and field exploration. This research use descriptive quantitative research design and using survey/questionnaire methods and documentation studies in collecting data. The results of data analysis using descriptive percentages obtained a tutorial learning indicator value of 67.5% which was included in the "moderate" category and the field exploration indicator obtained a value of 75.8% in the "high" category. This shows that the Wurung Crater Geosite is superior in the preparation and provision of techniques, facilities, and learning media to support field exploration activities than in the provision of guide/interpreter facilities as well as the quality and quantity of guides/interpreters. But overall it can be concluded that the Wurung Crater Geosite has the potential for educational tourism which is included in the "high" category with the acquisition of an accumulated value of two indicators of 72.3%.

Ecological connectivity analysis based on the fish community in Jeongan Stream

This study focused on the longitudinal connectivity analysis, based on fish communities in the aspect of spatial variations of 34 sites from upstream to downstream. The Fish Assessment Index (FAI), based on ecological guilds and species composition, was applied to compare the ecological health among the sampling sites. The total number of 35 fish species, were sampled during the study period with dominant species of <i>Zacco platypus</i> (35.4%) and <i>Zacco koreanus</i> (11.8%). Cluster analysis showed that all sites were categorized as 4 distinct group communities (A, B, C, D). Non-metric multidimensional scaling analysis showed distinct difference between upstream (A, B) and downstream groups (C, D). Indicator Value Analysis (IndVal method), conducted to identify indicator species within each group, indicated that the species favoring upstream environments Rhynchocypris oxycephalus for the Group A and Iksookimia koreensis for the Group B. In contrast, the analysis indicated that the species with a preference for downstream habitats Pseudogobio esocinus for the Group C and Carassius auratus for the Group D. Ecological health, based on the FAI scores, showed a declining pattern toward the downstream, along with an increasing proportion of tolerant species and omnivores within the fish community. Overall these findings suggest the compositions of fish communities, as four groups, were modified by the weir structures and organic matter, nutrient pollutions.

Amphibians of the genus Rana in the steppe zone of Ukraine: population status, distribution, and ecological features

Frogs of the genus Rana Linnaeus, 1758 are represented in the steppe zone of Ukraine by their southernmost populations. The distribution of brown frogs in the steppe zone of Ukraine is closely related to the floodplain forests of major rivers (Dnipro, Dnister, Danube, Southern Bug, Oril, Samara, Donets, etc.). The paper presents for the first time data on the distribution, ecological and population features, habitats, specifics of reproduction and development of brown frogs. New habitats of R. arvalis were found in the floodplain habitats of the lower reaches of the Dnipro River in Kherson Oblast and populations were confirmed in Dnipropetrovsk and Kirovohrad oblasts. The southern border is intrazonal. The new southernmost localities are described from Kherson Oblast (the villages of Pravi Solontsi and Krynky). The habitats belong to forest type habitats (G). The mean abundance of frogs is 5–10 individuals per 1 km of route and can reach 50 individuals per 10 m2 during the spawning season (Black Forest Reserve, Kirovohrad Oblast). The breeding season is in late March to early April at air temperatures of +3–4 to 8–12°C and water temperatures of +7–9°C. The mating process is short. The Dnipro isolates of R. arvalis may be of relict nature, form a series of refugia and be of important historical and indicator value. Given the overall reduction in the range of R. arvalis within its core area, active populations in the south can be valuable reserves for the conservation of the species and the sustainability of steppe biodiversity. Two other species, R. temporaria and R. dalmatina, were not found and their habitat within the steppe zone has not yet been confirmed. As typical forest species, they are common closer to the forest-steppe zone. Given the current state of brown frog populations in the steppe zone of Ukraine, their low numbers and isolation, they need regional protection along with their habitats. The issue of determining the origin of the identified populations in order to form an idea of the historical and genetic value of the southernmost populations of brown frogs in Ukraine remains promising.

Assessing Reaeration Rate Equations for Modelling Dissolved Oxygen of Pusu River in Malaysia

Many authors reported high variability in the prediction of reaeration rates by various equations, leading to uncertainty in the estimation of the reaeration rate for a river. Due to this uncertainty, it is essential to identify a suitable equation to predict the dissolved oxygen (DO) concentration of the river in concern. Pusu River in Malaysia receives sewage discharges and suffers from land-clearing activities and stormwater-related pollution. Pusu River is a small river, but highly important in terms of demography and geographic location. As such, it is required to identify a suitable reaeration rate equation for predicting its DO concentration, which indicates the overall health of a river. The purpose of this study is to assess the suitability of reaeration rate equations to predict Dissolved Oxygen (DO) concentrations of the Pusu River. The water quality analysis simulation program (WASP) model was employed to model the DO of the Pusu River. Reaeration rates calculated from the available 31 equations were given input in the model, and errors in prediction were calculated in terms of Root Mean Square (RMS) error and R2 for every equation. It was revealed that Neguluscu and Rojanski (1969) equation using depth and velocity as the variables performed best among all the equations. It produced a minimum RMS error of 0.17 and 0.09 mg/L in calibration and validation data, respectively. R2 values for predicted-observed plots were 0.98 and 0.97 in these two data sets using the equation. Based on overall Performance Indicator Values (PIVs), reaeration rate equations with depth and velocity as the variables performed better than the other equations with more variables for Pusu River. This study provided important information to accurately model the DO of the Pusu River for future simulation of different scenarios.

The holistic evaluation system of R&D results under the circular economy conditions

The object of the research is a holistic economic evaluation system of R&D results under the circular economy conditions. The system is based on the example of an innovative product – a three-wheeled electric scooter for disabled people, developed by specialists of the Lviv Polytechnic National University (Ukraine). For this purpose, the prospects and problems of the market of the analyzed product in the context of circular economy development are studied and its market place is determined. The price indicators of the R&D result are substantiated based on the aggregation of cost, competitive and income methodological components of the holistic evaluation system, taking into account the provisions of the circular economy. Financial indicators of the project for implementing the R&D result based on the proposed holistic evaluation system are formed. The applied value of the developed holistic evaluation system is to provide the evaluator (developer, consumer, investor) with a range of price indicator values, among which one can choose the necessary, based on contractual conditions, market changes, etc. Unlike the existing methodological developments in the field of pricing for R&D results, the proposed holistic system makes it possible to aggregate the current evaluation approaches. Such aggregation is based on determining and choosing the optimum product price from a set of possible (suitable for the corresponding product, market, business, etc.). The system provides comprehensive economic evaluation, creates the basis for developing flexible management solutions and effective forecasting under the circular economy conditions

«Цифровой двойник» населения Арктики в демографических исследованиях и управлении развитием территорий

The article considers “digital twins” of the population as a tool for socio-demographic research and territorial management. The experience of creating digital twins of the population and interactive web-sites devoted to demographic issues is systematized. A methodology for creating a digital twin of the Arctic population is proposed, based on three methodological principles: consideration of the hierarchy of territories, spatial representation of data, and combining demographic statistics with new digital data sources. The author has developed the Digital twin of the Arctic population — an interactive website (dashboard) containing detailed data on the Arctic population, including municipal and settlement levels. It includes demographic statistics, census results and data from digital platforms. The Digital twin of the Arctic population covers such issues as the size, dynamics and composition of the population, resettlement, natural and migration movement, labor and employment, transport movements, science and education, and the impact of the pandemic on demographic processes. Tools of ranking, multivariate analysis, clustering and forecasting of indicator values are implemented for researchers. From the viewpoint of state and municipal management, the main interest is the demographic profiles of regions and territories, reflecting up-to-date information about the demographic situation. Using the Digital twin of the Arctic population, the author draws conclusions about the spatial patterns of the demographic development of the Russian Arctic.

The Effect of Using the STAD (Student Teams Achievement Division) Cooperative Model Assisted by Finger Puppets on Students' Learning Motivation

Background: The ability of students to listen to stories from teachers and then be able to tell them again is not easy, and it will not be as expected. Because students' comprehension abilities vary when receiving and studying the story's content, teachers need a learning model to improve their students' storytelling abilities. In reality, class III students at State Elementary School 5 Pulang Pisau cannot concentrate and are interested in learning using the storytelling method. Aim: This research aims to determine the effect of using the STAD-type cooperative model assisted by finger puppets on motivation to learn Indonesian, especially in improving the storytelling skills of class III students at State Elementary School 5 Pulang Pisau. Method: This research uses a quantitative experimental approach. The research sample comprised 19 class III students at State Elementary School 5 Pulang Pisau. Results and Discussion: The research results show that (1) There is a positive influence that the STAD type cooperative method assisted by finger puppets has on the storytelling skills of class III students because the results Wilcoxon test analysis on all students has a value of Asymp.Sig. (2 Tailed) of 0.000 > 0.05. (2) There is a difference in the average indicator value for students before treatment, namely 13.5, and after treatment, the average value is 24.05. Conclusion: Based on the discussion, it can be concluded that using the STAD-type cooperative method assisted by finger puppet media positively affects students' motivation and storytelling skills.

Soil Microbial Communities in Pseudotsuga sinensis Forests with Different Degrees of Rocky Desertification in the Karst Region, Southwest China

Rocky desertification (RD), a natural and human-induced process of land degradation in karst areas, has become the primary ecological disaster and one of the obstacles to sustainable ecological development in southwest China. Nevertheless, the variation of soil physical and chemical properties, bacterial and fungal communities, and their relationships in RD forests remains limited. Therefore, soil samples were collected from forests under four degrees of RD (NRD, non-RD; LRD, light RD; MRD, moderate RD; and SRD, severe RD) and subjected to high-throughput sequencing of 16S rRNA and ITS1 genes. The results showed a significant reduction in bacterial richness and diversity, while fungal richness and diversity decreased markedly and then showed a balanced trend with the increase in RD degree, indicating that bacteria and fungi did not present the same dynamics in response to the process of RD. The bacterial communities were dominated by Proteobacteria, Actinobacteria, Acidobacteria, and Chloroflexi, while the fungal communities were dominated by Basidiomycota, Ascomycota, and Mortierellomycota. The PCoA and NMDS demonstrated significant differences in microbial communities in study sites, among which the fungal communities in non-RD forest and LRD forest clustered together, suggesting that fungal communities were more stable than bacteria in RD forest. The db-RDA, Mantel test, and random forest model confirmed the important role of soil BD, pH, SOC, AN, and AP in driving microbial diversity and communities. The IndVal analysis suggested that Chloroflexi, Patescibacteria, Atheliales, and Cantharellales with high indicator values were identified as potential bio-indicators for RD forests. This study could not only improve our understanding of bacterial and fungal community dynamics across RD gradients, but also could provide useful information for the further use of microorganisms as indicators to reflect the environmental changes and ecosystem status during forest RD.

Biological remediation treatments improve the health of a mixed contaminated soil before significantly reducing contaminant levels.

The remediation of mixed contaminated soil is challenging as it often requires actions to minimize metal-induced risks while degrading organic contaminants. Here, the effectiveness of different bioremediation strategies, namely, rhizoremediation with native plant species, mycoremediation with Pleurotus ostreatus spent mushroom substrate, and biostimulation with organic by-products (i.e., composted sewage sludge and spent mushroom substrate), for the recovery of a mixed contaminated soil from an abandoned gravel pit was studied. The combination of biostimulation and rhizoremediation led to the most significant increase in soil health, according to microbial indicator values. The application of composted sewage sludge led to the highest reduction in anthracene and polychlorinated biphenyls concentrations. None of the strategies managed to decrease contamination levels below regulatory limits, but they did enhance soil health. It was concluded that the biological remediation treatments improved soil functioning in a short time, before the concentration of soil contaminants was significantly reduced.

Оценка продуктивности и качества селекционных номеров ежи сборной

Cock’s foot as an early-ripening, highly nutritious cereal is a valuable fodder crop being demanded in fodder production. Under favorable environmental conditions of moisture and nutrition, this crop becomes a complete feed with an average energy nutrition of more than 10 MJ of exchangeable energy in 1 kg of dry matter and a crude protein content of 17-19 %. The aim of our study was to investigate and isolate promising selection numbers with high yields of dry matter, good quality of fodder with the highly adaptive resistance to various abiotic and biotic stress factors. The study material was four promising selection numbers in the breeding nursery as SN 10/18 (control), SN 5/18, SN 8/18, and SN 16/18. In three investigation years, we gave prominence by fodder productivity to selection samples SN 8/18 and SN 5/18, dry matter of which yielded 25.4 and 20.4 t/ha exceeding the control sample (19.2 t/ha) by 6.2 and 1.2 t/ha or 32.3 % and 6.3 %, respectively. The crude protein content in dry matter of the studied numbers ranged from 12.7 to 13.5 %. According to this indicator, the selection samples surpassed the control (12.3 %). The highest indicator value was found for SN 16/18. SN 8/18 was best in terms of crude protein yields summarized for three years (3.3 t/ha). The selection samples that showed high results in the experiment will be involved into the breeding process as sources of economically valuable traits.

Optimisation of process parameters for improving surface quality in laser powder bed fusion

Surface quality is one of the critical factors that affect the performance of a laser powder bed fusion part. Optimising process parameters in process design is an important way to improve surface quality. So far, a number of optimisation methods have been presented within academia. Each of these methods can work well in its specific context. But they were established on a few special surfaces and may not be capable to produce satisfying results for an arbitrary part. Besides, they do not consider the simultaneous improvement of the quality of multiple critical surfaces of a part. In this paper, an approach for optimising process parameters to improve the surface quality of laser powder bed fusion parts is proposed. Firstly, Taguchi optimisation is performed to generate a small number of alternative combinations of the process parameters to be optimised. Then, actual build and measurement experiments are conducted to obtain the quality indicator values of a certain number of critical surfaces under each alternative combination. After that, a flexible three-way technique for order of preference by similarity to ideal solution is used to determine the optimal combination of process parameters from the generated alternatives. Finally, a case study is presented to demonstrate the proposed approach. The demonstration results show that the proposed approach only needs a small amount of experimental data and takes into account the simultaneous improvement of the quality of multiple critical surfaces of an arbitrary part.

Turning the wheel: Measuring circularity in Swedish automotive products

The transition towards a circular economy necessitates the development of tools for evaluating circularity. This paper proposes an approach with three important indicators—industrial waste, energy use, and IT material waste—to solve the challenge of evaluating circularity in the Swedish automobile industry. Each indicator includes a number of scores and sub-scores allowing for a thorough evaluation of circularity at product level. Qualitative and quantitative data are gathered to calculate scores for individual aspects of the indicators, which are then combined into an overall product score using a weighted average, and associated with an accuracy measurement reflecting the quality of the input data. The sensitivity of circularity indicator values to data availability underscores the importance of accuracy metrics, while placing a priority on simplicity, usefulness, and adaptability. This framework incorporates knowledge from scientific literature, business reports, and sustainability specialists. The result is an overall product circularity score. Such a scorecard can be crucial in accelerating the transition to circularity and sustainability since it highlights areas that need improvement. The framework's development incorporates feedback from sustainability experts, while interviews with industry professionals and data testing ensure its practicality for companies. The framework is designed to be adaptable and scalable to suit industry requirements. Companies are encouraged to adopt it as an internal tool and take ownership to drive circularity initiatives effectively.