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With the help of basic physics, the application of computer algorithms in the form of recent advances such as machine learning and neural networking in textile Industry has been discussed in this review. Scientists have linked the underlying structural or chemical science of textile materials and discovered several strategies for completing some of the most time-consuming tasks with ease and precision. Since the 1980s, computer algorithms and machine learning have been used to aid the majority of the textile testing process. With the rise in demand for automation, deep learning, and neural networks, these two now handle the majority of testing and quality control operations in the form of image processing.

The state-of-the-art of artificial intelligence (AI) applications in the textile sector is reviewed in this paper. Based on several research problems and AI-based methods, the current literature is evaluated. The research issues are categorized into three categories based on the operation processes of the textile industry, including yarn manufacturing, fabric manufacture and coloration.

AI-assisted automation has improved not only machine efficiency but also overall industry operations. AI's fundamental concepts have been examined for real-world challenges. Several scientists conducted the majority of the case studies, and they confirmed that image analysis, backpropagation and neural networking may be specifically used as testing techniques in textile material testing. AI can be used to automate processes in various circumstances.

This research conducts a thorough analysis of artificial neural network applications in the textile sector.

The paper aims to solve the problem of personnel intrusion identification within the limits of high-speed railways. It adopts the fusion method of millimeter wave radar and camera to improve the accuracy of object recognition in dark and harsh weather conditions.

This paper adopts the fusion strategy of radar and camera linkage to achieve focus amplification of long-distance targets and solves the problem of low illumination by laser light filling of the focus point. In order to improve the recognition effect, this paper adopts the YOLOv8 algorithm for multi-scale target recognition. In addition, for the image distortion caused by bad weather, this paper proposes a linkage and tracking fusion strategy to output the correct alarm results.

Simulated intrusion tests show that the proposed method can effectively detect human intrusion within 0–200 m during the day and night in sunny weather and can achieve more than 80% recognition accuracy for extreme severe weather conditions.

(1) The authors propose a personnel intrusion monitoring scheme based on the fusion of millimeter wave radar and camera, achieving all-weather intrusion monitoring; (2) The authors propose a new multi-level fusion algorithm based on linkage and tracking to achieve intrusion target monitoring under adverse weather conditions; (3) The authors have conducted a large number of innovative simulation experiments to verify the effectiveness of the method proposed in this article.

The overall objective of this study is envisaged to provide decision makers with actionable insights and access to multi-risk maps for the most in-danger stave churches (SCs) among the existing 28 churches at high spatial resolution to better understand, reduce and mitigate single- and multi-risk. In addition, the present contribution aims to provide decision makers with some information to face the exacerbation of the risk caused by the expected climate change.

Material and data collection started with the consultation of the available literature related to: (1) SCs' conservation status, (2) available methodologies suitable in multi-hazard approach and (3) vulnerability leading indicators to consider when dealing with the impact of natural hazards specifically on immovable cultural heritage.

The paper contributes to a better understanding of place-based vulnerability with local mapping dimension also considering future threats posed by climate change. The results highlight the danger at which the SCs of Røldal, in case of floods, and of Ringebu, Torpo and Øye, in case of landslide, may face and stress the urgency of increasing awareness and preparedness on these potential hazards.

The contribution for the first time aims to homogeneously collect and report all together existing spread information on architectural features, conservation status and geographical attributes for the whole group of SCs by accompanying this information with as much as possible complete 2D sections collection from existing drawings and novel 3D drawn sketches created for this contribution. Then the paper contributes to a better understanding of place-based vulnerability with local mapping dimension also considering future threats posed by climate change. Then it highlights the danger of floods and landslides at which the 28 SCs are subjected. Finally it reports how these risks will change under the ongoing impact of climate change.

The purpose of this paper is to systematically review the history and current state of lesson study (LS) in Germany. In particular, this paper describes the development of LS over time and its stakeholders.

Conducting a systematic literature review, we searched three scientific databases and Google Scholar, examined 806 results and included 50 articles in our final sample, which we analyzed systematically.

The spread of LS in Germany can be divided into three phases, characterized by their own LS projects as well as their own ways of understanding LS. Although interest in LS has increased significantly in recent years, it is only present at a small number of schools and universities in Germany if compared internationally. Furthermore, this paper identifies the so-called learning activity curves as a tool frequently used for observation and reflection that appears to be unknown outside German-speaking countries.

This paper may act as an outline for countries without large-scale LS projects and with limited support from policymakers. The experience from Germany demonstrates the outcomes and challenges that can arise in such a situation and shows how unique LS features and proceedings have emerged.

Polymer laser powder bed fusion (PBF-LB/P) is an additive manufacturing technology that is sustainable due to the possibility of recycling the powder multiple times and allowing the fabrication of gears without the aid of support structures and subsequent assembly. However, there are constraints in the process that negatively affect its adoption compared to other additive technologies such as material extrusion to produce gears. This study aims to demonstrate that it is possible to overcome the problems due to the physics of the process to produce accurate mechanism.

Technological aspects such as orientation, wheel-shaft thicknesses and degree of powder recycling were examined. Furthermore, the evolving tooth profile was considered as a design parameter to provide a manufacturability map of gear-based mechanisms.

Results show that there are some differences in the functioning of the gear depending on the type of powder used, 100% virgin or 50% virgin and 50% recycled for five cycles. The application of a groove on a gear produced with 100% virgin powder allows the mechanism to be easily unlocked regardless of the orientation and wheel-shaft thicknesses. The application of a specific evolutionary profile independent of the diameter of the reference circle on vertically oriented gears guarantees rotation continuity while preserving the functionality of the assembled mechanism.

In the literature, there are various studies on material aging and reuse in the PBF-LB/P process, mainly focused on the powder deterioration mechanism, powder fluidity, microstructure and mechanical properties of the parts and process parameters. This study, instead, was focused on the functioning of gears, which represent one of the applications in which this technology can have great success, by analyzing the two main effects that can compromise it: recycled powder and vertical orientation during construction.

Building information modeling (BIM) is mostly limited to the design phase where two parallel processes exist, i.e. creating 2D-drawings and BIM. Towards the end of the design process, BIM becomes obsolete as focus shifts to producing static 2D-drawings, which leads to a lack of trust in BIM. In Scandinavia, a concept known as Total BIM has emerged, which is a novel “all-in” approach where BIM is the single source of information throughout the project. This paper's purpose is to investigate the overall concept and holistic approach of a Total BIM project to support implementation and strategy work connected to BIM.

Qualitative data were collected through eight semi-structured interviews with digitalization leaders from the case study project. Findings were analyzed using a holistic framework to BIM implementation.

The Total BIM concept was contingent on the strong interdependences between commonly found isolated BIM uses. Four main success factors were identified, production-oriented BIM as the main contractual and legally binding construction document, cloud-based model management, user-friendly on-site mobile BIM software and strong leadership.

A unique case is studied where BIM is used throughout all project phases as a single source of information and communication platform. No 2D paper drawings were used on-site and the Total BIM case study highlights the importance of a new digitalized construction process.

District-university partners increasingly rely on “grow-your-own” licensure programs to address teacher shortages. Because vacancies in special education represent a chronic issue, our district-university partnership developed LEAP – the Licensed Educators’ Accelerated Pathway, successfully preparing 26 paraprofessionals as special education teachers (SEs). We describe a model university-district partnership in which we collaborated to design and implement paraprofessionals’ SE licensure program.

In this general review, we describe a district-university partnership collaboration that resolved barriers experienced by paraprofessionals working toward licensure in special education (Essential #4, Reflection and Innovation). The specialized design and partnership solutions were grounded in SE preparation research literature.

25 (28 entered the program and 25 completed) paraprofessionals from one large urban and several regional districts completed special education licensure through LEAP. Slightly more than half of LEAP participants were Black or Hispanic (see Table 1), contributing to the diversification of SE workforce. University-district partnership was successful in designing and delivering a program that allowed participants: a) to remain employed, b) attend evening classes in their geographic region or online, c) complete all field experiences in sponsoring districts (Essential #2) and d) receive concierge advising from a “completion coach.” We describe solutions to barriers experienced by paraprofessionals and advocate for district-university collaboration to address chronic teacher shortages.

Limitations include lack of data on success of program completers during their first year of teaching as they began this work in Fall 2023. Further, because the participating district was large and urban, generalization of program details for small and rural districts is difficult.

Practical tips for developing grow-your-own special education licensure programs are providing. Detailed descriptions of barriers candidates experienced and ways the district-university partners resolved these issues are included. Programs like the one described has the potential to positively impact teacher pipeline issues.

The program described provided highly-trained teachers to fill chronic vacancies in special education in three participating districts/agencies. Because students receiving special education services are at risk for school failure and are disproportionately impacted by teacher turnover, addressing this area through grow-your-own licensure programs represents a diversity, equity and inclusion initiative. Further, upskilling diverse paraprofessionals to licensed teacher roles represent an economic boost, which they might not otherwise have achieved.

Available research literature signals alarm over persistent teacher shortages in hard-to-staff districts and lack of diversity in the teacher workforce, but few published accounts describe successful programs. Partner collaboration fostered a re-imagining of course formatting and delivery to accommodate adult learners, avoiding problems often reported with alternative programs.

As an advanced manufacturing method, additive manufacturing (AM) technology provides new possibilities for efficient production and design of parts. However, with the continuous expansion of the application of AM materials, subtractive processing has become one of the necessary steps to improve the accuracy and performance of parts. In this paper, the processing process of AM materials is discussed in depth, and the surface integrity problem caused by it is discussed.

Firstly, we listed and analyzed the characterization parameters of metal surface integrity and its influence on the performance of parts and then introduced the application of integrated processing of metal adding and subtracting materials and the influence of different processing forms on the surface integrity of parts. The surface of the trial-cut material is detected and analyzed, and the surface of the integrated processing of adding and subtracting materials is compared with that of the pure processing of reducing materials, so that the corresponding conclusions are obtained.

In this process, we also found some surface integrity problems, such as knife marks, residual stress and thermal effects. These problems may have a potential negative impact on the performance of the final parts. In processing, we can try to use other integrated processing technologies of adding and subtracting materials, try to combine various integrated processing technologies of adding and subtracting materials, or consider exploring more efficient AM technology to improve processing efficiency. We can also consider adopting production process optimization measures to reduce the processing cost of adding and subtracting materials.

With the gradual improvement of the requirements for the surface quality of parts in the production process and the in-depth implementation of sustainable manufacturing, the demand for integrated processing of metal addition and subtraction materials is likely to continue to grow in the future. By deeply understanding and studying the problems of material reduction and surface integrity of AM materials, we can better meet the challenges in the manufacturing process and improve the quality and performance of parts. This research is very important for promoting the development of manufacturing technology and achieving success in practical application.

This paper aims to propose a simulation-based performance evaluation model for the drone-based delivery of aid items to disaster-affected areas. The objective of the model is to perform analytical studies, evaluate the performance of drone delivery systems for humanitarian logistics and can support the decision-making on the operational design of the system – on where to locate drone take-off points and on assignment and scheduling of delivery tasks to drones.

This simulation model captures the dynamics and variabilities of the drone-based delivery system, including demand rates, location of demand points, time-dependent parameters and possible failures of drones’ operations. An optimization model integrated with the simulation system can update the optimality of drones’ schedules and delivery assignments.

An extensive set of experiments was performed to evaluate alternative strategies to demonstrate the effectiveness for the proposed optimization/simulation system. In the first set of experiments, the authors use the simulation-based evaluation tool for a case study for Central Florida. The goal of this set of experiments is to show how the proposed system can be used for decision-making and decision-support. The second set of experiments presents a series of numerical studies for a set of randomly generated instances.

The goal is to develop a simulation system that can allow one to evaluate performance of drone-based delivery systems, accounting for the uncertainties through simulations of real-life drone delivery flights. The proposed simulation model captures the variations in different system parameters, including interval of updating the system after receiving new information, demand parameters: the demand rate and their spatial distribution (i.e. their locations), service time parameters: travel times, setup and loading times, payload drop-off times and repair times and drone energy level: battery’s energy is impacted and requires battery change/recharging while flying.

The e-commerce boom presents new challenges for last-mile delivery (LMD), which may be mitigated by new delivery technologies. This paper evaluates the impact of mobile parcel lockers (MPL) on costs and CO₂ equivalent (CO₂e) emissions in existing LMD networks, which include home delivery and shipments to stationary parcel lockers.

To describe customers’ preferences, we design a multinomial logit model based on recipients’ travel distance to pick-up locations and availability at home. Based on route cost estimation, we define the operating costs for MPLs. We devise a mathematical model with binary decision variables to optimize the location of MPLs.

Our study demonstrates that integrating MPLs leads to additional cost savings of 8.7% and extra CO₂e emissions savings of up to 5.4%. Our analysis of several regional clusters suggests that MPLs yield benefits in highly populous cities but may result in additional emissions in more rural areas where recipients drive longer distances to pick-ups.

This paper designs a suitable operating model for MPLs and demonstrates environmental and economic savings. Moreover, it adds recipients’ availability at home to receive parcels improving the accuracy of stochastic demand. In addition, MPLs are evaluated in the context of several regional clusters ranging from large cities to rural areas. Thus, we provide managerial guidance to logistics service providers how and where to deploy MPLs.