Search

The existing joint extraction methods for entity relationships in knowledge data only target specific fields or datasets, which may have insufficient coverage for large-scale and diverse manufacturing knowledge data. In order to achieve more accurate and efficient joint extraction of manufacturing knowledge data entity relationship, an improved method based on BERT algorithm is proposed in this paper. This method constructs a manufacturing specific knowledge graph, treating the extraction of quantitative knowledge as the extraction of manufacturing entity attributes, thereby achieving joint extraction of knowledge reasoning and data entity relationships. The improved BERT algorithm was used to establish a distribution feature set of entity relationships in manufacturing knowledge data, and a manufacturing specific knowledge graph was constructed, providing an effective way to analyze and extract entity relationships in manufacturing data, thereby helping decision-makers better understand knowledge in the manufacturing field and improving production efficiency and quality. The test results show that the knowledge graph generated by the method has good expression ability and strong logical reasoning ability, and the running time required by the application of the method is only 12 s, indicating that it can realize the joint clustering extraction of entity relationships in manufacturing knowledge data more efficiently and accurately. The innovation of this paper lies in applying BERT algorithm to joint extraction of entity relationship of manufacturing knowledge data, and improving the algorithm to improve the accuracy and efficiency of extraction, providing a new solution for the construction and application of manufacturing knowledge graph. [ABSTRACT FROM AUTHOR]

The circular economy plays a key role in the wider transition to a low-carbon built environment. Materials are critical in this transition, yet there is limited information about their current use in the built environment in many regions. This explorative study investigated circular economy in the Australian construction materials industry using a three-stage mixed-method approach. The first stage was to map actors and their practices and challenges related to material supply, use, and end of life. This involved 20 interviews with stakeholders and a workshop. The second stage was to assess key materials stocks and flows to identify the volume of the challenge through existing databases and consultation with industry stakeholders. The third stage was to understand the current state of material circularity at industry-leading examples. This was investigated through 13 interviews across two case studies, alongside site visits. These complementary research methods and stages provided findings into material circularity potential within the residential construction sector from both a macroperspective and a microperspective. The results included that new materials being used in construction are more than double the flow of waste out, showing that stocks of materials in use are growing rapidly but that data gaps are extensive. There was a focus on material reduction for cost-savings and sustainability, but there was significant opportunity for other circular economy principles, such as rethinking construction techniques. Further, in the context of a highly volatile industry, circularity requires a focus on material-specific institutional arrangements. The contribution to knowledge on construction materials and their supply chain provides fundamental insights that are required for the transition toward a circular economy, where the residential construction sector (not just in Australia but globally) would more readily reduce, reuse, recycle and recover resources, as well as being less reliant on virgin material use. [ABSTRACT FROM AUTHOR]

AbstractThis column considers challenges and opportunities AI generative chatbots pose to proprietary library databases. It briefly reviews evolution from paper library indices to Web-based databases then reasons why current chatbots pose greater challenges to database relevancy than when Web engines first emerged. Library databases and free chatbots are compared in terms of identifying information needs, and locating, evaluating, and using information. Q/A with EBSCO are collected on challenges and opportunities chatbots provide them. Discussion centering around questions intended for database vendors ensues, along with a conclusion on potential information literacy benefits if library databases adopt chatbot search platforms. [ABSTRACT FROM AUTHOR]

Nearshoring is a phenomenon that has gained prominence in Mexico over the last 2 years, where companies have faced problems in meeting customer demand due to a service level and limited inventory space. Previous studies in aggregate planning did not consider the possibility of allowing rental of extra warehouse space if needed with a concurrent uncertainty in demand. Therefore, to address this gap in the research, an improved optimization model for multi-product and multi-period aggregate planning with uncertainty in demands given an area of inventory space is proposed. A set of cases based on real industry data were solved and compared to a model where no warehouse space is allowed to be rented. The results are improvements related to production costs and customer demand satisfaction. In addition, the model will help managers of manufacturing companies to determine the minimum inventory space required to effectively meet demand. [ABSTRACT FROM AUTHOR]

A carbon emission factor (CEF) database is required for the basis of carbon emission calculation in construction projects. However, the default values for existing CEF databases cannot cover the complex resources involved in a construction project. Therefore, this paper proposes a three-step method to guide the establishment of an extensible CEF database for the construction industry, including (1) data collection and parser, (2) data extension, and (3) data encoding and storage. The data extension mechanisms provide the supply chain perspective considering temporal issues and the accounting perspective to streamline the process. Aiming to address the lack of a comprehensive CEF database for the construction industry in China, this paper uses this method to establish a carbon emission factor database for the Chinese construction industry (CEFD for CCI). This database is open and free with 646 CEFs, including five parts: energy, human, material, machinery, and greenspace. This paper provides a way for developing and less developed countries to establish an expandable CEF database, which benefits the parser, extension, encoding, and storage of new resources, as well as computer access. [ABSTRACT FROM AUTHOR]

The recent Federal Trade Commission (FTC) and Department of Justice (DOJ) action against Monument Inc. for selling patient data, is just the tip of the iceberg. Monument Inc. positions itself as a treatment provider (the website home page says it provides "therapy" for alcoholism) but in its extensive terms of use, it says it is not a treatment provider. And in fact, since the FTC/DOJ action this spring, Monument radically changed its website, removing the offending promise of "confidentiality" which it breached, but still selling services (lowest price $15/month). [ABSTRACT FROM AUTHOR]

The developments in global market have allowed the firms with high competitiveness at the local level to gain competitive advantages. This case has boosted interest in industrial agglomerations. The approach of clustering, which draws attention to the importance of local economy in the global economy, has been implemented by many countries as a development strategy. In the early years of the Republic, in Çorum, which is located on historical trade routes, production activities were carried out in houses or in workshops in the form of small businesses. Upon the inclusion of Çorum among the priority regions for development in 1972, industrialization activities accelerated in the province. With the transition from the policy of an import‐substitution industrialization to an open growth model in 1980, the development of decentralization areas was encouraged in Turkey. Accordingly, thanks to the incentives provided, Corum rapidly industralized after 1980 and also became one of the provinces known as Anatolia Tigers. This study aims to determine the concentration level of the sub‐sectors in the manufacturing class within the scope of the Statistical Classification of Economic Activity in Corum. In this purpose, the study utilized the data on the distribution of producers across provinces in the TOBB Industry Database. Three star analysis was conducted on the data obtained. According to the results of the three star analysis, while 13 out of 129 sectors operating in Çorum province on the basis of 4 codes in NACE code categorization were classified as mature clusters, 19 were categorized as potential clusters and 18 evaluated to be candidate clusters. [ABSTRACT FROM AUTHOR]

This research sought to develop a structured methodology for transferring resilience resources and safety innovation across industrial sectors, specifically, from aviation to maritime. As transportation sectors struggle to adapt to new economic realities and seek to prosper in new operational contexts there is a need to preserve resources and invest in change initiatives which will derive meaningful impact. A structured methodology to guide a principled transfer of safety solutions across sectors would be a sustainable method of improving the resilience of the sector. An action research approach was adopted. A five-step methodology was developed in cooperation with three maritime organisations to identify challenges and resilience resources from aviation which could be feasibly transferred and implemented. Five steps were identified as being key to a principled transfer of resilience resources from aviation to maritime. They were as follows: (1) industry comparison and database of aviation resilience resources; (2) maritime user needs and gap analysis, and resilience resources evaluation and selection; (3) scenarios production and resources mapping onto scenarios; (4) feasibility analysis; and (5) implementation plan. The results highlight the utility of combining bottom-up (identifying problems) and top-down (identifying a database of resources) approaches at the outset. A comprehensive workshop-based feasibility analysis is also key to ensuring the identified resources can be effectively implemented in the destination sector. [ABSTRACT FROM AUTHOR]

The reverse engineering (RE) process is often necessary in today's engineering and medical industries. Expertise in measurement technology, data processing, and CAD modeling is required to ensure accurate reconstruction of an object's geometry. However, errors are generated at every stage of geometric reconstruction, affecting the dimensional and geometric accuracy of the final 3D-CAD model. In this article, the geometry of reconstructed models was measured using contact and optical methods. The measurement data representing 2D profiles, 3D point clouds, and 2D images acquired in the reconstruction process were saved to a stereolithography (STL) model. The reconstructed models were then subjected to a CAD modeling process, and the accuracy of the parametric modeling was evaluated by comparing the 3D-CAD model to the 3D-STL model. Based on the results, the model used for clamping and positioning parts to perform the machining process and the connecting rod provided the most accurate mapping errors. These models represented deviations within ±0.02 mm and ±0.05 mm. The accuracy of CAD modeling for the turbine blade model and the pelvis part was comparable, presenting deviations within ±0.1 mm. However, the helical gear and the femur models showed the highest deviations of about ±0.2 mm. The procedures presented in the article specify the methods and resolution of the measurement systems and suggest CAD modeling strategies to minimize reconstruction errors. These results can be used as a starting point for further tests to optimize CAD modeling procedures based on the obtained measurement data. [ABSTRACT FROM AUTHOR]

This is the second article in a new series designed to provide readers with insight into educating nurses about evidence-based decision-making. It builds on AJN 's award-winning previous series—Evidence-Based Practice, Step by Step and EBP 2.0: Implementing and Sustaining Change (to access both series, go to http://links.lww.com/AJN/A133). This follow-up series will address how to teach and facilitate learning about the evidence-based practice (EBP) and quality improvement (QI) processes and how they impact health care quality. This series is relevant for all nurses interested in EBP and QI, especially DNP faculty and students. The brief case scenario included in each article describes one DNP student's journey. This article, the second in a series on how to teach and facilitate learning about evidence-based practice and quality improvement, discusses optimizing clinical inquiry, using data to describe a clinical problem, and strategically developing a focused clinical question. Supplemental digital content is available in the text. [ABSTRACT FROM AUTHOR]

This paper uses relevant mathematical statistical models to verify the interactive effect between population mobility and the high-quality development of the manufacturing industry based on the panel data of 43 counties in the Fujian province from 2007 to 2021. The results show that (1) the inflow areas of population flow in the Fujian province are mainly concentrated in the southeast region; (2) there is mutual promotion between population mobility and the high-quality development of the manufacturing industry in the Fujian province, and the population mobility in adjacent areas has a significant promotion effect on the high-quality development of the local manufacturing industry; and (3) heterogeneity results show that after 2011, the interaction effect between population mobility and the high-quality development of the manufacturing industry has declined, and population inflow has a stronger role in promoting the high-quality development of the manufacturing industry than population outflow. The conclusions of this study are of great significance to the Fujian province for implementing a reasonable population policy and promoting the coordinated development of manufacturing enterprises. [ABSTRACT FROM AUTHOR]

The selection of the most suitable material is one of the key decisions to be made during the design stage of a manufacturing process. Traditional approaches, such as Ashby maps based on material properties, are widely used in industry. However, in the production of multi-material components, the criteria for the selection can include antagonistic approaches. The aim of this work is to implement a methodology based on the results of process simulations for several materials and to classify them by applying an advanced data analytics method based on machine learning (ML)—in this case, the support vector regression (SVR) or multi-criteria decision-making (MCDM) methodology. Specifically, the multi-criteria optimization and compromise solution (VIKOR) was combined with entropy weighting methods. To achieve this, a finite element model (FEM) was built to evaluate the extrusion force and the die wear during the multi-material co-extrusion process of bimetallic Ti6Al4V-AZ31B billets. After applying SVR and VIKOR in combination with the entropy weighting methodology, a comparison was established based on material selection and the complexity of the methodology used. The results show that the material chosen in both methodologies is very similar, but the MCDM method is easier to implement because there is no need for evaluating the error of the prediction model, and the time required for data preprocessing is less than the time needed when applying SVR. This new methodology is proven to be effective as an alternative to traditional approaches and is aligned with the new trends in industry based on simulation and data analytics. [ABSTRACT FROM AUTHOR]

The measurement of Functional Reach Test (FRT) is a widely used assessment tool in various fields, including physical therapy, rehabilitation, and geriatrics. This test evaluates a person's balance, mobility, and functional ability to reach forward while maintaining stability. Recently, there has been a growing interest in utilizing sensor-based systems to objectively and accurately measure FRT results. This systematic review was performed in various scientific databases or publishers, including PubMed Central, IEEE Explore, Elsevier, Springer, the Multidisciplinary Digital Publishing Institute (MDPI), and the Association for Computing Machinery (ACM), and considered studies published between January 2017 and October 2022, related to methods for the automation of the measurement of the Functional Reach Test variables and results with sensors. Camera-based devices and motion-based sensors are used for Functional Reach Tests, with statistical models extracting meaningful information. Sensor-based systems offer several advantages over traditional manual measurement techniques, as they can provide objective and precise measurements of the reach distance, quantify postural sway, and capture additional parameters related to the movement. [ABSTRACT FROM AUTHOR]