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Most layer‐based rapid prototyping systems use polygonal models as input. In addition, the input polygonal models need to be manifold and water‐tight; otherwise the built objects may have defects or the building process may fail in some cases. This paper aims to present a regulation method of an arbitrarily complex polygonal model for rapid prototyping and manufacturing applications.

The method is based on a semi‐implicit representation of a solid model named the layered depth‐normal images (LDNI), which sparsely encodes the shape boundary of a polygonal model in three orthogonal directions. In the method, input polygonal models or parametric equations are first converted into LDNI models. A regulation operator based on the computed LDNI models is presented. A volume tiling technique is developed for very complex geometries and high accuracy requirements. From the processed LDNI model, an adaptive contouring method is presented to construct a cell representation that includes both uniform and octree cells. Finally, two‐manifold and water‐tight polygonal mesh surfaces are constructed from the cell representation.

The LDNI‐based mesh regulation operation can be robust due to its simplicity. The accuracy of the generated regulated models can be controlled by setting LDNI pixel width. Parallel computing techniques can be employed to accelerate the computation in the LDNI‐based method. Experimental results on various CAD models demonstrate the effectiveness and efficiency of our approach for complex geometries.

The input polygonal model is assumed to be closed in our method. The regulated polygonal model based on our method may have a big file size.

A novel mesh regulation method is presented in this paper. The method is suitable for rapid prototyping and manufacturing applications by achieving a balance between simplicity, robustness, accuracy, speed and scalability. This research contributes to the additive manufacturing development by providing a digital data preparation method and related tools.

Support structures are often needed in additive manufacturing (AM) to print overhangs. However, they are the extra materials that must be removed afterwards. When the supports have many contacts to the model or are even enclosed inside some concavities, removing them is very challenging and has a risk of damaging the part. Therefore, the purpose of this paper is to develop a new type of tree-support, named Escaping Tree-Support (ET-Sup), which tries to build all the supports onto the build plate to minimize the number of contact points.

The methodology is to first classify the support points into three categories: clear, obstructed and enclosed. A clear point has nothing between it and the build plate; an obstructed point is not clear, but there exists a path for it to reach the build plate; and an enclosed point has no way to reach the build plate. With this classification, the path for the obstructed points to come clear can be found through linking them to the clear points. All the operations are performed efficiently with the help of a ray representation.

The method is tested on different overhang features, including a lattice ball and a mushroom shape with a concave cap. All the supports generated for the examples can find their way to the build plate, which looks like they are escaping from the model. The computation time is around one second for these cases.

This is the first time truly realizing this “escaping” property in the generation of tree-like support structures. With this ET-Sup, it is expected that the AM industries can reduce the manufacturing lead time and save much labor work in post-processing.

In the implementation of large-size additive manufacturing (AM), the large printing area can be established by using the tiled and fixed multiple printing heads or the single dynamic printing head moving in the x–y plane, which requires a layer decomposition after the mesh slicing to generate segmented infill areas. The data processing flow of these schemes is redundant and inefficient to some extent, especially for the processing of complex stereolithograph (STL) models. It is of great importance in improving the overall efficiency of large-size AM technics software by simplifying the redundant steps. This paper aims to address these issues.

In this paper, a method of directly generating segmented layered infill areas is proposed for AM. Initially, a vertices–mesh hybrid representation of STL models is constructed based on a divide-and-conquer strategy. Then, a trimming–mapping procedure is performed on sliced contours acquired from partial surfaces. Finally, to link trimmed open contours and inside-signal square corners as segmented infill areas, a region-based open contour closing algorithm is carried out in virtue of the developed data structures.

In virtue of the proposed approach, the segmented layered infill areas can be directly generated from STL models. Experimental results indicate that the approach brings us the good property of efficiency, especially for complex STL models.

The proposed approach can generate segmented layered infill areas efficiently in some cases.

The region-based layered infill area generation approach discussed here will be a supplement to current data process technologies in large-size AM, which is very suitable for parallel processing and enables us to improve the efficiency of large-size AM technics software.

Given an intersection-free mesh surface S, the paper introduces a method to thicken S into a solid H located at one side of S. By such a surface-to-solid conversion operation, industrial users are able to fabricate a designed (or reconstructed) surface by rapid prototyping.

The paper first investigates an implicit representation of the thickened solid H according to an extension of signed distance function. After that, a partial surface reconstruction algorithm is proposed to generate the boundary surface of H, which retains the given surface S on the resultant surface.

Experimental tests show that the thickening results generated by the method give nearly uniform thickness and meanwhile do not present shape approximation error at the region of input surface S. These two good properties are important to the industrial applications of solid fabrication.

The input polygonal model is assumed to be intersection-free, where models containing self-intersection will lead to invalid thickening results.

A novel robust operation is to convert a freeform open surface into a solid by introducing no shape approximation error. A new implicit function gives a compact mathematical representation, which can easily handle the topological change on the thickened solids. A new polygonization algorithm generates faces for the boundary of thickened solid meanwhile retaining faces on the input open mesh.

A new method of hollowing rapid prototype models based on STL models and their cross‐sectional contours is presented to meet the demands of hollowed prototypes in casting and rapid prototype manufacturing. Offsetting along the Z‐axis and cross‐sectional contour offsetting are employed to perform the hollowing operation. The process performs two‐dimensional Boolean operations on the polygons made by the offset contours of cross‐sectional contours instead of three‐dimensional offsetting of the STL models. This hollowing operation is especially suitable for hollowing STL models with free‐form surfaces. Detailed algorithms are described to generate the correct offset contours of an STL model. Adopting this method, the hollowing process is dramatically simplified and becomes more efficient. This method has been verified by practical case studies, and it is proved that this simplified hollowing operation can reduce the prototype build time and cost.

A simplified approach for estimating weld lines, vent locations and fill times for resin transfer molding applications in non‐planar geometry is presented. The molding parts are treated as polyhedral spaces for which the concept of Voronoi diagram and shortest paths is utilized to predict the formation of weld lines, location of vents and filling times. The approach is based purely on geometrical considerations and on previously established observations that it is possible to treat the resin flow inside the mold as partly radial and partly channel‐like. The proposed procedure is geared towards software implementation, but it enables one to gain more insight into the process before detailed and time‐consuming calculations are attempted.

New media is reshaping mediated communication. This paper aims to examine whether the online community is concerned about ethical issues in citizen journalism.

The study uses critical thematic analyses to examine 1,402 comments posted in response to two YouTube videos of teenage girl molestation in India. This method was appropriate, as it will show how public reacts to information disseminated by common citizens and also show whether ethics are related to citizen journalism.

Results show that although some viewers questioned the cameraperson’s and the passerby’s morality, several supportive comments praised the cameraperson’s presence of mind and courage. Furthermore, it shows that while some viewers vilified the victim, others advocated a more prudent response. This shows ambiguity regarding ethics in cyberspace. The mixed reactions present strong evidence to challenge the idealistic and exceedingly rational original notion of the public sphere as homogenous or integrated on issues of public concern. Instead, result exhibits an emergence of pluralistic, intersecting and contending publics that are created by new communication technologies like the internet.

The study was specific to a particular context thereby lacking generalizability. However, it implies further investigation of social agency and the underlying politics in the move from local to global.

These findings necessitate a reconceptualization of cyberspace ethics to accommodate the new publics that have materialized from new media technologies.

The purpose of this study is to investigate and demonstrate the advancements achieved in the field of chest X-ray image captioning through the utilization of dynamic convolutional encoder–decoder networks (DyCNN). Typical convolutional neural networks (CNNs) are unable to capture both local and global contextual information effectively and apply a uniform operation to all pixels in an image. To address this, we propose an innovative approach that integrates a dynamic convolution operation at the encoder stage, improving image encoding quality and disease detection. In addition, a decoder based on the gated recurrent unit (GRU) is used for language modeling, and an attention network is incorporated to enhance consistency. This novel combination allows for improved feature extraction, mimicking the expertise of radiologists by selectively focusing on important areas and producing coherent captions with valuable clinical information.

In this study, we have presented a new report generation approach that utilizes dynamic convolution applied Resnet-101 (DyCNN) as an encoder (Verelst and Tuytelaars, 2019) and GRU as a decoder (Dey and Salemt, 2017; Pan et al., 2020), along with an attention network (see Figure 1). This integration innovatively extends the capabilities of image encoding and sequential caption generation, representing a shift from conventional CNN architectures. With its ability to dynamically adapt receptive fields, the DyCNN excels at capturing features of varying scales within the CXR images. This dynamic adaptability significantly enhances the granularity of feature extraction, enabling precise representation of localized abnormalities and structural intricacies. By incorporating this flexibility into the encoding process, our model can distil meaningful and contextually rich features from the radiographic data. While the attention mechanism enables the model to selectively focus on different regions of the image during caption generation. The attention mechanism enhances the report generation process by allowing the model to assign different importance weights to different regions of the image, mimicking human perception. In parallel, the GRU-based decoder adds a critical dimension to the process by ensuring a smooth, sequential generation of captions.

The findings of this study highlight the significant advancements achieved in chest X-ray image captioning through the utilization of dynamic convolutional encoder–decoder networks (DyCNN). Experiments conducted using the IU-Chest X-ray datasets showed that the proposed model outperformed other state-of-the-art approaches. The model achieved notable scores, including a BLEU_1 score of 0.591, a BLEU_2 score of 0.347, a BLEU_3 score of 0.277 and a BLEU_4 score of 0.155. These results highlight the efficiency and efficacy of the model in producing precise radiology reports, enhancing image interpretation and clinical decision-making.

This work is the first of its kind, which employs DyCNN as an encoder to extract features from CXR images. In addition, GRU as the decoder for language modeling was utilized and the attention mechanisms into the model architecture were incorporated.

The purpose of this paper is to propose an appropriate symbolic representation, as well as its metaphorical interpretation, to illustrate the special role of information in the knowledge acquisition process.

Besides the literature review, this is a speculative study based on a symbolic and metaphorical point of view.

The proposed symbolic representation was derived from the conceptual designation of information “as a flow” and, accordingly, by the corresponding redrawing of the data-information-knowledge-wisdom (DIKW) pyramid. The knowledge acquisition process is symbolically represented by the growth of a “tree of knowledge” which is planted on a “data earth,” filled with “information sap” and lit by the rays of the “sun of the mind,” a new symbol of the concept of wisdom in the DIKW model. As indicated, a key concept of this metaphorical interpretation is the role of “information sap” which rises from the roots of the “tree of knowledge” to the top of the tree and it is recognized as an invisible link between “world of data” and “world of knowledge.” This concept is also proposed as a new symbolic representation of the DIKW model.

On the basis of specific symbolic-metaphorical representation, this paper provides a relatively new concept of information which may help bridge observed gaps in the understanding of information in various scientific fields, as well as in its understanding as an objective or subjective phenomenon.