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This study aims to investigate the fabrication of solid ankle foot orthoses (SAFOs) using fused deposition modeling (FDM) printing technology. It emphasizes cost-effective 3D scanning with the Kinect sensor and conducts a comparative analysis of SAFO durability with varying thicknesses and materials, including polylactic acid (PLA) and carbon fiber-reinforced (PLA-C), to address research gaps from prior studies.

In this study, the methodology comprises key components: data capture using a cost-effective Microsoft Kinect® Xbox 360 scanner to obtain precise leg dimensions for SAFOs. SAFOs are designed using CAD tools with varying thicknesses (3, 4, and 5 mm) while maintaining consistent geometry, allowing controlled thickness impact investigation. Fabrication uses PLA and PLA-C materials via FDM 3D printing, providing insights into material suitability. Mechanical analysis uses dual finite element analysis to assess force–displacement curves and fracture behavior, which were validated through experimental testing.

The results indicate that the precision of the scanned leg dimensions, compared to actual anthropometric data, exhibits a deviation of less than 5%, confirming the accuracy of the cost-effective scanning approach. Additionally, the research identifies optimal thicknesses for SAFOs, recommending a 4 and 5 mm thickness for PLA-C-based SAFOs and an only 5 mm thickness for PLA-based SAFOs. This optimization enhances the overall performance and effectiveness of these orthotic solutions.

This study’s innovation lies in its holistic approach, combining low-cost 3D scanning, 3D printing and computational simulations to optimize SAFO materials and thickness. These findings advance the creation of cost-effective and efficient orthotic solutions.

The research evaluated the feasibility of 3D dynamic fit utilizing female compression tops by comparatively analyzing the virtual and actual dynamic fit.

Six female participants were 3D body-scanned and photographed in compression tops in four types of athletic movements (pull-up, kettlebell swing, circle-crunch and sit-up). Fit measurements, waist cross-sectional areas, waist width, waist depth, numerical simulation of clothing pressure (kPa) and objective pressure measurements (kPa) were collected from 3D virtual animation, 3D fit scan data and actual photos with the four types of athletic motions. The data were comparatively investigated between virtual and actual dynamic fit.

The 3D-animated body was not reflected with human body deformation because only bone structure was changed while maintaining the constant forms of muscle and body surface in athletic movements. Due to this consistency of virtual dynamic fit, there were significant differences with the actual dynamic fit at the top length, shoulder width and waist cross-sectional areas. Also, the virtual dynamic pressure indicated significantly higher levels than the objective dynamic pressure while presenting no significant correlations at the front neckline, breast, lateral waist, upper back, back armhole and back waist.

This study is the first to verify multiple aspects of virtual dynamic fit using 3D digital technology. This study provided useful information about which aspects of the current virtual animation need to be improved to apply in the dynamic fit evaluation.

This paper aims to prompt ideas amongst readers (especially librarians) about how they can become active partners in knowledge dissemination amongst concerned user groups by implementing 3D printing technology under the “Makerspace.”

The paper provides a brief account of various tools and techniques used by veterinary and animal sciences institutions for information dissemination amongst the stakeholders and associated challenges with a focus on the use of 3D printing technology to overcome the bottlenecks. An overview of the 3D printing technology has been provided following the instances of use of this novel technology in veterinary and animal sciences. An initiative of the University Library, Guru Angad Dev Veterinary and Animal Sciences University, Ludhiana, to harness the potential of this technology in disseminating information amongst livestock stakeholders has been discussed.

3D printing has the potential to enhance learning in veterinary and animal sciences by providing hands-on exposure to various anatomical structures, such as bones, organs and blood vessels, without the need for a cadaver. This approach enhances students’ spatial understanding and helps them better understand anatomical concepts. Libraries can enhance their visibility and can contribute actively to knowledge dissemination beyond traditional library services.

The ideas about how to harness the potential of 3D printing in knowledge dissemination amongst livestock sector stakeholders have been elaborated. This promotes creativity amongst librarians enabling them to think how they can engage in knowledge dissemination thinking out of the box.

This paper aims to propose a robust method for non-rigid point set registration, using the Gaussian mixture model and accommodating non-rigid transformations. The posterior probabilities of the mixture model are determined through the proposed integrated feature divergence.

The method involves an alternating two-step framework, comprising correspondence estimation and subsequent transformation updating. For correspondence estimation, integrated feature divergences including both global and local features, are coupled with deterministic annealing to address the non-convexity problem of registration. For transformation updating, the expectation-maximization iteration scheme is introduced to iteratively refine correspondence and transformation estimation until convergence.

The experiments confirm that the proposed registration approach exhibits remarkable robustness on deformation, noise, outliers and occlusion for both 2D and 3D point clouds. Furthermore, the proposed method outperforms existing analogous algorithms in terms of time complexity. Application of stabilizing and securing intermodal containers loaded on ships is performed. The results demonstrate that the proposed registration framework exhibits excellent adaptability for real-scan point clouds, and achieves comparatively superior alignments in a shorter time.

The integrated feature divergence, involving both global and local information of points, is proven to be an effective indicator for measuring the reliability of point correspondences. This inclusion prevents premature convergence, resulting in more robust registration results for our proposed method. Simultaneously, the total operating time is reduced due to a lower number of iterations.

Rebar is the prime component of reinforced concrete structures, and rebar monitoring is a time-consuming and technical job. With the emergence of the fourth industrial revolution, the construction industry practices have evolved toward digitalization. Still, hesitation remains among stakeholders toward the adoption of advanced technologies and one of the significant reasons is the unavailability of knowledge frameworks and implementation guidelines. This study aims to investigate technical factors impacting automated monitoring of rebar for the understanding, confidence gain and effective implementation by construction industry stakeholders.

A structured study pipeline has been adopted, which includes a systematic literature collection, semistructured interviews, pilot survey, questionnaire survey and statistical analyses via merging two techniques, i.e. structural equation modeling and relative importance index.

The achieved model highlights “digital images” and “scanning” as two main categories being adopted for automated rebar monitoring. Moreover, “external influence”, “data-capturing”, “image quality”, and “environment” have been identified as the main factors under “digital images”. On the other hand, “object distance”, “rebar shape”, “occlusion” and “rebar spacing” have been highlighted as the main contributing factors under “scanning”.

The study provides a base guideline for the construction industry stakeholders to gain confidence in automated monitoring of rebar via vision-based technologies and effective implementation of the progress-monitoring processes. This study, via structured data collection, performed qualitative and quantitative analyses to investigate technical factors for effective rebar monitoring via vision-based technologies in the form of a mathematical model.

Amid rapid technological progress, the construction industry is embracing Construction 4.0, redefining work practices through emerging technologies. However, the implications of Construction 4.0 technologies to enhancing well-being are still poorly understood. Particularly, the challenge lies in selecting technologies that critically contribute to well-being enhancement. Therefore, this study aims to evaluate the implications of Construction 4.0 technologies to enhancing well-being.

A list of Construction 4.0 technologies was identified from a national strategic plan on Construction 4.0, using Malaysia as a case study. Fourteen construction industry experts were selected to evaluate the implications of Construction 4.0 technologies on well-being using fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). The expert judgment was measured using linguistic variables that were transformed into fuzzy values. Then, the collected data was analyzed using the following analyses: fuzzy TOPSIS, Pareto, normalization, sensitivity, ranking performance and correlation.

Six Construction 4.0 technologies are critical to enhancing well-being: cloud & real-time collaboration, big data & predictive analytics, Internet of Things, building information modeling, autonomous construction and augmented reality & virtualization. In addition, artificial intelligence and advanced building materials are recommended to be implemented simultaneously as a very strong correlation exists between them.

The novelty of this study lies in a comprehensive understanding of the implications of Construction 4.0 technologies to enhancing well-being. The findings can assist researchers, industry practitioners and policymakers in making well-informed decisions to select Construction 4.0 technologies when targeting the enhancement of the overall well-being of the local construction industry.

Organisations are investing in systems such as product lifecycle management (PLM) to support product development, collaboration across complex supply chains and to provide a framework for digital transformation. Graduates of apparel programmes would benefit from a knowledge of PLM to help realise the opportunities that PLM offers. The purpose of this paper is to report on an educational research project that used PLM as a context for practice-based learning and as a mechanism to update the learning experience and stimulate the development of future practice.

This paper reports on the experiences, critical reflections and data from an action research study to establish a learning community through an educational partnership for PLM software within an undergraduate fashion business course. The cohort of the first year of the intervention (n = 28) is the main study population.

The findings indicate that PLM provided a stimulating learning context supportive of a detailed understanding of current industry practice, critical and innovative thinking and the development of a professional identity.

The opportunity for the development of both industry and educational practice is outlined.

A general introduction to PLM provides important information to support and advance Fashion Industry 4.0. Educational partnerships can reduce barriers to the integration of advanced technologies into the higher education curriculum.

Applications of PLM are under researched in textiles and apparel. The paper contributes to the broadening of the knowledge base of PLM and its potential to achieve strategic transformation of the sector.

Accurate and automatic clothing pattern making is very important in personalized clothing customization and virtual fitting room applications. Clothing pattern generating as well as virtual clothing simulation is an attractive research issue both in clothing industry and computer graphics.

Physics-based method is an effective way to model dynamic process and generate realistic clothing animation. Due to conceptual simplicity and computational speed, mass-spring model is frequently used to simulate deformable and soft objects follow the natural physical rules. We present a physics-based clothing pattern generating framework by using scanned human body model. After giving a scanned human body model, first, we extract feature points, planes and curves on the 3D model by geometric analysis, and then, we construct a remeshed surface which has been formatted to connected quad meshes. Second, for each clothing piece in 3D, we construct a mass-spring model with same topological structures, and conduct a typical time integration algorithm to the mass-spring model. Finally, we get the convergent clothing pieces in 2D of all clothing parts, and we reconnected parts which are adjacent on 3D model to generate the basic clothing pattern.

The results show that the presented method is a feasible way for clothing pattern generating by use of scanned human body model.

The main contribution of this work is twofold: one is the geometric algorithm to scanned human body model, which is specially conducted for clothing pattern design to extract feature points, planes and curves. This is the crucial base for suit clothing pattern generating. Another is the physics-based pattern generating algorithm which flattens the 3D shape to 2D shape of cloth pattern pieces.

This paper reviews the pros and cons of different parametric modeling methods, which can provide a theoretical reference for parametric reconstruction of 3D human body models for virtual fitting.

In this study, we briefly analyze the mainstream datasets of models of the human body used in the area to provide a foundation for parametric methods of such reconstruction. We then analyze and compare parametric methods of reconstruction based on their use of the following forms of input data: point cloud data, image contours, sizes of features and points representing the joints. Finally, we summarize the advantages and problems of each method as well as the current challenges to the use of parametric modeling in virtual fitting and the opportunities provided by it.

Considering the aspects of integrity and accurate of representations of the shape and posture of the body, and the efficiency of the calculation of the requisite parameters, the reconstruction method of human body by integrating orthogonal image contour morphological features, multifeature size constraints and joint point positioning can better represent human body shape, posture and personalized feature size and has higher research value.

This article obtains a research thinking for reconstructing a 3D model for virtual fitting that is based on three kinds of data, which is helpful for establishing personalized and high-precision human body models.

The purpose of the study is to compare methodologies for mapping a historic building, with image capture by smartphones and drones, using photogrammetric techniques for three-dimensional (3D) modeling of the structure. Processes and products are also analyzed, as well as possibilities for storing and visualizing data for structuring a cadastre of historical and artistic heritage are studied.

For mapping with smartphones, the overlapping of photographs was guaranteed, with data acquisition using three different cameras, on the same date as the aerial survey. The models were made from different combinations of camera use. For storage, a conceptual model based on ISO 19.152:2012 is proposed, which was implemented in the MongoDB, resulting in a database for storage. The visualization was carried out on the Cesium ion platform.

The results indicate that the terrestrial 3D reconstruction using smartphones is an efficient alternative to the historical and artistic cadastre, presenting texture quality superior to the aerial survey in a shorter production time. When dealing with the conceptual model, the LADM (Land Administration Domain Model) standardization guarantees interoperability and facilitates data exchange. In addition, it proved to be flexible for the creation of thematic profiles, supporting their effective storage. The insertion of data in the visualization platform was simple and effective, and it even generated sharing links for visualization of the models.

The study analyses a low-cost method with the use of easily accessible devices, with a combination of methodologies and applied techniques. The data storage and visualization method is also simple and flexible, suitable for application in the cadastre of historical heritage.