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Apart from the geometries to be dealt with, rapid prototyping (RP) of heterogeneous objects requires additional material information to be processed. This generally involves a large amount of information to be processed simultaneously. The robustness and efficiency problems, which seem less critical in homogeneous solid fabrications, become an issue. The direct impetus of this paper is to present robust and efficient algorithms for RP of heterogeneous objects.

The robustness is benefited from using the proposed non‐manifold heterogeneous cellular model, which guarantees gap‐free material depositions around material interfaces. The efficiency enhancement is achieved by eliminating repetitive boundary intersections and using a heuristic material interrogation approach.

By using the proposed algorithms, the robustness and efficiency of RP of heterogeneous objects can be improved. It is found that an average 30 percent efficiency improvement is obtained using the proposed heuristic material interrogation approach.

Non‐manifold heterogeneous cell representation (HC‐Rep) is used in RP fields for the first time. Based on the HC‐Rep, the robustness and efficiency of RP of heterogeneous object is addressed in this paper.

The representation of Heterogeneous Object (HO) is divided into two categories: Data model (DM) and material evaluation paradigm (MEP). A hybrid methodology with geometry model and volumetric dataset to represent heterogeneous properties is proposed in this paper. Geometry model of an object can guarantee the accuracy of the final HO slices; and volumetric dataset lends the flexible manipulability and other advantages to HO representation. Two MEPs, namely distance field (DF) based and Fixed Reference Features & Active Grading Source(s) (FRF&AGS) are presented to facilitate the process of HO representation according to the designer)s input parameters. The DM can be modified interactively with users until the final satisfactory result is obtained. In this paper, a scheme of HO slicing is described. In this method, we utilize the slices contour of geometrical model as constraint to reconstruct the HO slices, which can theoretically achieve the same accuracy with the geometrical shape. Some examples of Heterogeneous object represented with our scheme are provided.

The purpose of this paper is to consider arguments both for and against intellectual property (IP) rights that are premised on each of two conceptions of the information commons that attributes either moral value or disvalue to its preservation.

The methodology is the philosophically standard one of reflective equilibrium. The author considers the argument for a morally protected information commons that is grounded in Locke's famous proviso limiting original acquisition of material property to situations that leave enough of the resource to others and Hardin's famous argument that holding material property in common leads to overuse and depletion – a Tragedy of the commons. In particular, the arguments are evaluated according to whether they cohere with ordinary foundational commitments.

The author argues that neither conception of the commons is directly applicable to information objects and hence is relevant with respect to the issue of whether legal protection of IP rights is morally justified.

The identification of key differences between material objects and information objects that shows the irrelevance of these two leading conceptions in resolving the general issue of whether legal protection of IP rights is justified.

Accurate and rapid tracking and counting of building materials are crucial in managing on-site construction processes and evaluating their progress. Such processes are typically conducted by visual inspection, making them time-consuming and error prone. This paper aims to propose a video-based deep-learning approach to the automated detection and counting of building materials.

A framework for accurately counting building materials at indoor construction sites with low light levels was developed using state-of-the-art deep learning methods. An existing object-detection model, the You Only Look Once version 4 (YOLO v4) algorithm, was adapted to achieve rapid convergence and accurate detection of materials and site operatives. Then, DenseNet was deployed to recognise these objects. Finally, a material-counting module based on morphology operations and the Hough transform was applied to automatically count stacks of building materials.

The proposed approach was tested by counting site operatives and stacks of elevated floor tiles in video footage from a real indoor construction site. The proposed YOLO v4 object-detection system provided higher average accuracy within a shorter time than the traditional YOLO v4 approach.

The proposed framework makes it feasible to separately monitor stockpiled, installed and waste materials in low-light construction environments. The improved YOLO v4 detection method is superior to the current YOLO v4 approach and advances the existing object detection algorithm. This framework can potentially reduce the time required to track construction progress and count materials, thereby increasing the efficiency of work-in-progress evaluation. It also exhibits great potential for developing a more reliable system for monitoring construction materials and activities.

The purpose of this study is to examine the interplay between the curatorial practices of consumers as collectors and the materiality of the collected objects. In particular, this study explores how the material substances of collected objects shapes curatorial practices and how the ongoing use of the collected objects challenges curatorial practices.

Taking advantage of the publicization of once-private collections on social media, we collect 111 YouTube videos created by plastic shoe aficionados. Drawing from visual anthropology and theorizations of materiality, we analyze consumer interactions with the objects they collect.

This study’s findings elucidate consumers’ interactions with the material substances of the objects they collect and demonstrate how these interactions shape the ways in which consumers curate their collections, including how they wear, care for, catalog, and display the collected objects.

Our findings have implications for theorization on consumer collections, consumer identity, and consumer participation in brand communities and are relevant for consumer researchers who study the interactions and relationships between consumers and consumption objects.

This study is the first to re-examine consumers as collectors to extend and update consumer research on the curatorial practices of physical, wearable collectibles. This study sets the foundations for further research to advance our understanding of consumers as collectors as well as to illuminate other theories and aspects of consumer research that consider consumer–object interactions.

This paper explores the role of institutional objects in the constitution of institutional logics. Institutional objects depend for their objectivity on the goods produced through those objects, such as economic models, passports, or sacred texts. The authors theorize institutional logics as grammars of valuation that institutionalize goods through institutional objects. The authors identify four value moments through which goods are objectified: institution, the instituting of a good, a belief and an imagination of its objective goodness; production, how the good is produced, what practices are productive of the good; evaluation, how good is the good, the practices and objects through which worth in terms of that good is determined, and territorialization, the domain of reference of the good, to what objects and practices a good can and does refer in its instantiations. The authors assess the adequacy of our model through an institutional object based on the good of “market value” – i.e., an options pricing model. The authors discuss the implications of these findings for institutional logical theory and the sociology of valuation.

This paper aims to develop a slice-based representation of geometry and material information of a multi-material object to be produced by additive manufacturing. Representation of complex heterogeneous material allowing for the additive manufacturing-based build of a wide range of objects that are limited only by the constraints of the manufacturing process.

Initial 3D CAD models are created with multiple and functionally graded materials using an assembly model to create a single part with well-defined material regions. These models are then sliced to create the geometry and material boundaries required for each layer to enable layer-by-layer fabrication.

A representation schema is proposed to add multi-material attributes to a sliced file for additive manufacturing using the combination of material index and material geometry region. A modified common layer interface data format is proposed to allow for representation of a wide range of homogeneous and heterogeneous material for each slice. This format allows for a generic input for tool paths to be generated for each material of the layer.

The proposed approach allows for slice data representation for any material combination that can be defined mathematically. Three different material types, namely, composite material, functionally graded materials and combination thereof, are provided as examples. These data form the input data for subsequent tool path planning.

Information models for the representation of product data are being developed as an international standard. However, the current application protocols focus on the representation of homogeneous objects only. This paper suggests an information model to represent heterogeneous objects using the information modeling methodology developed for ISO 10303. The data planning model is then extended to represent the two‐dimensional (2D) slice information using concepts from ISO 10303. The proposed formats are validated by physical realization of objects on two LM machines. This information model will help in providing a uniform base in the development of heterogeneous solid modeling systems. It will also equip the solid modeler with the ability to integrate with other applications and process planning in the domain of layered manufacturing.

The paper aims to provide an overview of the vocabulary for materiality which is used by practice‐based approaches to organizational knowing.

The overview is theoretically generated and is based on the anthology Knowing in Organizations: A Practice‐based Approach edited by Nicolini, Gherardi and Yanow. The overview is built by cross‐reading the analyses in this book. The intellectual traditions which are scrutinized all agree that action is materially embedded – objects and artifacts are central to both knowing and learning. But what is their understanding of materiality? The paper explores which concepts are used, how the interaction between social and material realities is presented, and the role materiality is perceived to have in relation to action.

Findings are that, within the practice‐based approach, common terms for materiality are “artifact” and “object”. The interaction between social and material realities is grasped as several processes: object‐oriented activity, symbolization, embodiment, performance, alignment and mediation. Material artifacts both stabilize and destabilize organizational action. They may ensure coordination, communication, and control, but they may also create disturbance and conflict.

The paper lists a range of options for conceptualizing how organizational action may be materially mediated. It points out that material entities may both stabilize and destabilize organizational action. It contributes to the further understanding of the tangible, artifactual and object‐related side of organizational knowing.

Advances in material agency driven by artificial intelligence (AI) have facilitated breakthroughs in material adaptivity enabling smart objects to autonomously provide individualized smart services, which makes smart objects act as social actors embedded in the real world. However, little is known about how material adaptivity fosters the infusion use of smart objects to maximize the value of smart services in customers' lives. This study examines the underlying mechanism of material adaptivity (task and social adaptivity) on AI infusion use, drawing on the theoretical lens of social embeddedness.

This study adopted partial least squares structural equation modeling (PLS-SEM), mediating tests, path comparison tests and polynomial modeling to analyze the proposed research model and hypotheses.

The results supported the proposed research model and hypotheses, except for the hypothesis of the comparative effects on infusion use. Besides, the results of mediating tests suggested the different roles of social embeddedness in the impacts of task and social adaptivity on infusion use. The post hoc analysis based on polynomial modeling provided a possible explanation for the unsupported hypothesis, suggesting the nonlinear differences in the underlying influencing mechanisms of instrumental and relational embeddedness on infusion use.

The formation mechanisms of AI infusion use based on material adaptivity and social embeddedness help to develop the business strategies that enable smart objects as social actors to exert a key role in users' daily lives, in turn realizing the social and economic value of AI.

This study advances the theoretical research on material adaptivity, updates the information system (IS) research on infusion use and identifies the bridging role of social embeddedness of smart objects as agentic social actors in the AI context.