Multiple Viewpoints Research Articles

The Trees Speak for Themselves

Elif Shafak's 2021 novel The Island of Missing Trees describes fictional events that occur on the real island of Cyprus during the war between the Greek and the Turkish inhabitants of the island. This story is told from multiple points of view at various points in time in both Cyprus and London, where the characters move to and live following the events of the war and their families’ disagreements with their relationship. What is unique about Shafak's storytelling is her use of a fig tree as a primary narrator of events. While the use of non-human narrators is not a new strategy, most of these occurrences involve animal speakers rather than plants or objects. In delivering a fiction narrative from the point of view of a fig tree, Elif Shafak's The Island of Missing Trees introduces readers to multispecies encounters by providing an example of how arboreal figures communicate and experience history alongside humans in an anthropocentric world, and further encourages prosocial behavior between human and non-human species. Based on Shafak's novel, theories of attentiveness and slow-violence, and studies on the effect of non-human narrators on readers, including these "non-living" narrators in widely accessible pieces of fiction not only informs audiences of the multispecies encounters that occur in everyday life, but also opens more avenues of multispecies conservation.

Estimating the lateral speed of a fast shock driven by a coronal mass ejection at the location of solar radio emissions

Fast coronal mass ejections (CMEs) can drive shock waves capable of accelerating electrons to high energies. These shock-accelerated electrons act as sources of electromagnetic radiation, often in the form of solar radio bursts. Recent findings suggest that radio imaging of solar radio bursts can provide a means to estimate the lateral expansion of CMEs and associated shocks in the low corona. Our aim is to estimate the expansion speed of a CME-driven shock at the locations of radio emission using 3D reconstructions of the shock wave from multiple viewpoints. In this study, we estimated the 3D location of radio emission using radio imaging from the Nançay Radioheliograph and the 3D location of a CME-driven shock. The 3D shock was reconstructed using white-light and extreme ultraviolet images of the CME from the Solar Terrestrial Relations Observatory, Solar Dynamics Observatory, and the Solar and Heliospheric Observatory. The lateral expansion speed of the CME-driven shock at the electron acceleration locations was then estimated using the approximate 3D locations of the radio emission on the surface of the shock. The radio bursts associated with the CME were found to reside at the flank of the expanding CME-driven shock. We identified two prominent radio sources at two different locations and found that the lateral speed of the shock was between $ $ and $ second $ at these locations. Such a high speed during the early stages of the eruption already indicates the presence of a fast shock in the low corona. We also found a larger ratio between the radial and lateral expansion speed compared to values obtained higher up in the corona. We estimated for the first time the 3D expansion speed of a CME-driven shock at the location of the accompanying radio emission. The high shock speed obtained is indicative of a fast acceleration during the initial stage of the eruption. This acceleration leading to lateral speeds in the range of $ second $ is most likely one of the key parameters contributing to the presence of metric radio emissions, such as type II radio bursts.

The fevers and the limits of creativity in journalism

The article below tries to highlight, from multiple points of view, the concept of creativity in journalism - a field with various possibilities of approach and interpretation of the concept, the author noting that all people are creative to the extent that they are beings endowed with spirit. The article will answer the question of whether the journalist can resort to fiction and imagination, without seriously affecting the journalistic text, or the approaches to the concept in the media field cannot always be interpreted unilaterally. At the same time, we will try to identify an answer to the question regarding the creativity that a journalist would need, based on the fact that currently, in the professional environment, we could not speak of a journalist, in the singular, but of journalists with very different specializations, who are required to perform work editorials from very diverse perspectives.

Reframing Implications of Social Presence in Asynchronous Online Learning

The impact of social presence on virtual learning experiences is of increased interest in educational research as teaching and learning transitions from traditional classrooms to online learning environments. Educators need to know more about how to design asynchronous learning experiences that will results in students’ abilities to infer the mental states of others and participate in social conflict monitoring through perceptions of various social cues, as occurs in non-virtual instruction. Findings in the study showed that students’ age and satisfaction with online learning were the two main variables shaping participants’ mental states in online learning environments. Participants who expressed that online learning was sometimes a satisfying experience were more likely to believe that instructors could not resolve social conflicts. Otherwise, participants with some asynchronous learning experience tended to believe that social conflicts could be resolved by instructors teaching ethical decision-making skills and presenting and discussing multiple points of view. The outcomes of this study emphasize how instructors can work toward building social, cognitive, and teaching presence in online learning environments and can inform future social presence research.

High-precision binocular camera calibration method based on a 3D calibration object.

A high-precision binocular camera calibration method is proposed to address the issues of poor calibration accuracy and large calibration errors in current practical applications. This method uses a triangular stereo sphere as the calibration object and employs steps, such as ellipse fitting, Cholesky decomposition, homography matrix solution, and nonlinear optimization, to compute the intrinsic and extrinsic parameters, distortion parameters, and relative pose of the binocular camera. Moreover, this method simplifies the correspondences between primitives, enabling simultaneous calibration of multiple viewpoint cameras. This method is also suitable for both binocular cameras consisting of two different structured monocular cameras and those composed of two image sensors within the same structure. Experimental results showed that this method outperforms traditional algorithms in terms of binocular camera calibration accuracy, calibration errors between left and right cameras, and robustness, resulting in a significant improvement in overall algorithm performance.

MultiSum: A Multi-Facet Approach for Extractive Social Summarization Utilizing Semantic and Sociological Relationships

Social summarization aims to provide summaries for a large number of social texts (called posts) about a single topic. To extract a summary, both the representation of post and summary selection method are crucial. Previous methods introduce social relation to enhance post embedding to mitigate the sparse representation due to its brief and informal expression. However, they ignore that there are multiple relations between posts. Besides, existing graph-based centrality calculation approaches tend to select posts from one aspect. This leads to facet bias especially when there are multiple viewpoints. In this paper, we propose a model named MultiSum to improve social summarization. Specifically, 1) We use graph convolutional networks to fuse text content with social and semantic relations to improve post representation; 2) The similarity between the summary and all aspects is incorporated into the centrality score during the selection phase, encouraging the model to pay attention to different facets. Experimental results on English and Chinese corpora support the effectiveness of this model. Furthermore, external evaluations by human experts and large language models demonstrate the validity of MultiSum in facet coverage and redundancy reduction.

DVANet: Disentangling View and Action Features for Multi-View Action Recognition

In this work, we present a novel approach to multi-view action recognition where we guide learned action representations to be separated from view-relevant information in a video. When trying to classify action instances captured from multiple viewpoints, there is a higher degree of difficulty due to the difference in background, occlusion, and visibility of the captured action from different camera angles. To tackle the various problems introduced in multi-view action recognition, we propose a novel configuration of learnable transformer decoder queries, in conjunction with two supervised contrastive losses, to enforce the learning of action features that are robust to shifts in viewpoints. Our disentangled feature learning occurs in two stages: the transformer decoder uses separate queries to separately learn action and view information, which are then further disentangled using our two contrastive losses. We show that our model and method of training significantly outperforms all other uni-modal models on four multi-view action recognition datasets: NTU RGB+D, NTU RGB+D 120, PKU-MMD, and N-UCLA. Compared to previous RGB works, we see maximal improvements of 1.5%, 4.8%, 2.2%, and 4.8% on each dataset, respectively. Our code can be found here: https://github.com/NyleSiddiqui/MultiView_Actions

GTMFuse: Group-attention transformer-driven multiscale dense feature-enhanced network for infrared and visible image fusion

Infrared and visible images captured by different devices can be seamlessly integrated into a single composite image through the application of image fusion techniques. However, many existing convolutional neural network-based methods for infrared and visible image fusion have exhibited limited capability for effectively amalgamating information from the source images. Consequently, we propose a group-attention transformer into the multiscale feature enhanced network for infrared and visible image fusion, which we abbreviate as GTMFuse. Specifically, GTMFuse employs multiscale dual-channel encoders to independently process the source image and extract multiscale features. Among the encoders, the group-attention transformer module is utilized to facilitate more comprehensive long-range feature dependency modeling at each scale. This innovative module seamlessly combines a fixed-direction stripe attention mechanism with channel attention and window attention, enabling comprehensive global long-range information capture and interaction with feature information across the source images. The multiscale features obtained from the group-attention transformer module are integrated into the fused image through a meticulously designed dense fusion block. Furthermore, this study introduces a novel dataset named HBUT-IV, encompassing surveillance images captured from multiple viewpoints. The HBUT-IV dataset serves as a valuable benchmark for assessing the efficacy of fusion methods. Extensive experiments are conducted on four datasets employing nine comparative methods, revealing the superior performance of the GTMFuse approach. The implementation code is accessible at https://github.com/XingLongH/GTMFuse.

Empty Nest Syndrome: You Might Be Next!!

The empty nest syndrome (ENS) has been a term used in psychology to denote the psychological symptoms that arise when the youngest child leaves the family for work or further studies causing a void in the family leaving the aged parents behind termed as the empty nest. There have been many theories posited to explain the empty nest and multiple view points exist regarding the phenomenon. This phenomenon was described in the 1940s and 1950s and the present review evaluates the existing literature on the ENS in the light of modern era conceptions of human development. The advent of neurobiology and better understanding of menopause and the hormonal changes that ensue have resulted in us having a greater insight into this phenomenon. There are many changes that a couple undergoes in mid life and these all contribute to the ENS in some way or another. Marital and family factors as well as the parent child relationship play a vital role in adjustment to the empty nest situation. This review also tries to explain the validity of a concept like ENS in the modern digital era and in the light of modern relationships and their effect on the mind of the people involved.

The Personal Experience of Systemic Violence, Social Stigma and Structural Vulnerability in The Spinning Heart by Donal Ryan

This article aims at examining how systemic violence is connected with social stigma and structural vulnerability in the social novel The Spinning Heart, which was published by the Irish writer Donal Ryan in 2012. This much lauded work describes the collapse of the Celtic Tiger and its devastating effects in a small rural town in Ireland from multiple viewpoints. Although there are twenty-one first-person narrators, one per chapter, Bobby Mahon stands out among them. In fact, the story of this construction foreman connects with the trajectories presented by the other characters. Through all of them, Ryan denounces the practices and procedures that powerful and privileged institutions, groups and individuals resort to in contemporary Ireland in order to assert control or authority over other less favoured members of society, thus fostering a climate of violence. Attention is drawn in this article to the nature of the patterns of aggression and hostility developed by the main characters in the novel but also to the adverse impact these unjust, oppressive and stigmatising patterns have on vulnerable subjects by burdening them physically, psychologically, culturally and financially. Michael Staudigl’s theories on systemic violence in Phenomenologies of Violence (2014), Imogen Tyler’s notions on social stigma in Stigma. The Machinery of Inequality (2020), Judith Butler’s ideas on structural vulnerability in Vulnerability in Resistance (2016) and Pierre Bourdieu’s views on patriarchy in Masculine Domination (2001) inform this work.

Vertically spliced tabletop light field cave display with extended depth content and separately optimized compound lens array.

Tabletop three-dimensional light field display is a kind of compelling display technology that can simultaneously provide stereoscopic vision for multiple viewers surrounding the lateral side of the device. However, if the flat panel light field display device is simply placed horizontally and displayed directly above, the visual frustum will be tilted and the 3D content outside the display panel will be invisible, the large oblique viewing angle will also lead to serious aberrations. In this paper, we demonstrate what we believe to be a new vertical spliced light field cave display system with an extended depth content. A separate optimization of different compound lens array attenuates the aberration from different oblique viewing angles, and a local heating fitting method is implemented to ensure the accuracy of fabrication process. The image coding method and the correction of the multiple viewpoints realize the correct construction of spliced voxels. In the experiment, a high-definition and precisely spliced 3D city terrain scene is demonstrated on the prototype with a correct oblique perspective in 100-degree horizontal viewing range. We envision that our research will provide more inspiration for future immersive large-scale glass-free virtual reality display technologies.

Can you trust Wikidata?

In order to use a value retrieved from a Knowledge Graph (KG) for some computation, the user should, in principle, ensure that s/he trusts the veracity of the claim, i.e., considers the statement as a fact. Crowd-sourced KGs, or KGs constructed by integrating several different information sources of varying quality, must be used via a trust layer. The veracity of each claim in the underlying KG should be evaluated, considering what is relevant to carrying out some action that motivates the information seeking. The present work aims to assess how well Wikidata (WD) supports the trust decision process implied when using its data. WD provides several mechanisms that can support this trust decision, and our KG Profiling, based on WD claims and schema, elaborates an analysis of how multiple points of view, controversies, and potentially incomplete or incongruent content are presented and represented.

Information-Theoretic Exploration for Adaptive Robotic Grasping in Clutter Based on Real-Time Pixel-Level Grasp Detection

Robust robotic grasping in clutter still remains a challenging problem despite its great practical value. This paper presents an information-theoretic exploration approach that aims to improve the grasp estimation quality in complex environment. First, a light-weight grasp detector that composed by inverted residual blocks and a pyramid pooling module is proposed to make more accurate pixel-wise predictions in real-time, which are then projected to the workspace. To measure the uncertainty of estimations in the workspace, a two-dimensional grasp entropy (2D-GE) is defined and Gaussian process is applied to regress the variation of the information gain that approximated by 2D-GEs. Finally, guided by the information gain, depth cost, and distance cost, our approach is able to actively collect and fuse estimations from multiple informative viewpoints through the exploration that finally converges to a refined best grasp, resulting an improved grasping performance with a higher success rate and environmental adaptability in clutter. Simulation and robotic experiment are both performed to demonstrate the effectiveness of our method and compare it to baselines.

VERI-D: A new dataset and method for multi-camera vehicle re-identification of damaged cars under varying lighting conditions

Vehicle re-identification (V-ReID) is a critical task that aims to match the same vehicle across images from different camera viewpoints. The previous studies have leveraged attribute clues, such as color, model, and license plate, to enhance the V-ReID performance. However, these methods often lack effective interaction between the global–local features and the final V-ReID objective. Moreover, they do not address the challenging issues in real-world scenarios, such as high viewpoint variations, extreme illumination conditions, and car appearance changes (e.g., due to damage or wrong driving). We propose a novel framework to tackle these problems and advance the research in V-ReID, which can handle various types of car appearance changes and achieve robust V-ReID under varying lighting conditions. Our main contributions are as follows: (i) we propose a new Re-ID architecture named global–local self-attention network, which integrates local information into the feature learning process and enhances the feature representation for V-ReID and (ii) we introduce a novel damaged vehicle Re-ID dataset called VERI-D, which is the first publicly available dataset that focuses on this challenging yet practical scenario. The dataset contains both natural and synthetic images of damaged vehicles captured from multiple camera viewpoints and under different lighting conditions. (iii) We conduct extensive experiments on the VERI-D dataset and demonstrate the effectiveness of our approach in addressing the challenges associated with damaged vehicle re-identification. We also compare our method to several state-of-the-art V-ReID methods and show its superiority.

Assessing the evolution of banking reputation literature: a bibliometric analysis

PurposeThe concept of banking reputation has gained significant attention due to its relevance in the banking industry. A strong reputation has become crucial for a bank’s success, as it affects trust, credibility and stakeholders' perceptions. However, understanding and managing reputation in the banking sector involves several challenges. This study aims to analyze the field of banking reputation research through bibliometric analysis.Design/methodology/approachIt explores the evolution of research in this area, identifies key journals, articles and authors, examines the main research streams, and identifies research fronts and opportunities for future advancement.FindingsThe findings reveal that banking reputation research has evolved over time, with multiple perspectives and viewpoints. Key journals and authors in the field are identified, and leading research streams are highlighted. The study also uncovers the conceptual and intellectual structure of the research domain, providing insights into the complex and multidimensional nature of banking reputation. Furthermore, the study emphasizes the importance of corporate social responsibility, sustainability practices and gender diversity in shaping a bank’s reputation. These factors play a significant role in attracting and retaining customers, accessing financial markets and securing funding.Research limitations/implicationsThe results contribute to the existing body of knowledge and provide researchers and practitioners with valuable insights for further exploration.Originality/valueThe paper concludes by outlining potential avenues for future research in the field of banking reputation.

Recent Advancements in α‐Ga2O3 Thin Film Growth for Power Semiconductor Devices via Mist CVD Method: A Comprehensive Review

AbstractThis review discusses the impact of alpha‐gallium oxide (α‐Ga2O3) on potential high‐power device applications. To date, there are high requirements for efficient high‐power delivery and low‐power loss device material in power industries. III‐VI oxide semiconductor family, α‐Ga2O3, is recognized as a promising, future power semiconductor material owing to its ultrawide bandgap of 5.3 eV, high breakdown field of 10 MV cm−1, and a large Baliga's figure of merit. A highly expected α‐Ga2O3 power semiconductor electronic device (Schottky barrier diode and field effect transistor) can perform better than conventional semiconductor materials Si, SiC, and GaN. However, there is a lack of research into using mist CVD to cultivate high‐quality α‐Ga2O3 for high‐power devices like FETs and SBDs. Currently, the mist CVD‐grown α‐Ga2O3 thin film power device is still in its early stages, and one of the main reasons for this is defects of the thin film, which impede material electron mobility. The purpose of writing this article is to provide an overview of the development of α‐Ga2O3 heteroepitaxial thin film by the mist CVD process for use in high‐power devices such as Schottky barrier diodes (SBD) and field effect transistors (MOSFET). 1. α‐Ga2O3 α‐Ga2O3. Furthermore, multiple viewpoints highlight the challenges and future trends toward device performance sustainability in a scientific society.

Negotiating the Postmodern Narrative Techniques in Life of Pi

The present paper attempts to analyse the complex and ambiguous phenomenon of the very movement of postmodernism in Yann Martel’s distinguished novel Life of Pi. Owing to the techniques and strategies employed in this novel, it can be called the true representative of postmodern fiction. As it breaks with realism and avoids rigid genre distinction, postmodernism deconstructs the wholeness and completeness associated with conventional storytelling ways. There is use of postmodern narrative as the novel is highly self-reflexive and Martel also experiments with intertextuality and historiographic metafiction. He weaves this novel withextraordinary and unusual events. By blending facts and fiction, he makes space for the readers for different interpretations. The contours of postmodern techniques such as fragmentation, metafiction, multiple points of view, advocacy of plurality of histories, and sheer rejection of grand narratives are used in this novel. Out here Martel delineates the chaotic condition of the postmodern world through Life of Pi.

Embracing a Perspective with the Dark Side: Using Second Wave Positive Psychology to Navigate Emotions Throughout Transformative Learning

While transformative learning often leads to positive experiences, it can also be a complex, emotionally turbulent process. The process for some can represent a messy and emotionally chaotic journey, where learners may find themselves in conflict with their emotional comfort zones as they question belief systems, who they are, how they see the world, interpret what happens to them, and consider multiple points of view to verify one’s truth and reality. This autoethnographic study focuses on a doctoral student’s interactions with varied cognitive, sociocultural, and emotional challenges throughout their educational and personal experiences. This study integrates Transformative Learning Theory with Ivtzan et al.’s (2016) second wave dark side positive psychology, introducing a dark side perspective to transformative learning. This approach aims to deepen the understanding of the entire emotional experience and offers guidance for navigating the transformative learning process.

“Frequently Asked Questions” About Genetic Engineering in Farm Animals: A Frame Analysis

Calls for public engagement on emerging agricultural technologies, including genetic engineering of farm animals, have resulted in the development of information that people can interact and engage with online, including “Frequently Asked Questions” (FAQs) developed by organizations seeking to inform or influence the debate. We conducted a frame analysis of FAQs webpages about genetic engineering of farm animals developed by different organizations to describe how questions and answers are presented. We categorized FAQs as having a regulatory frame (emphasizing or challenging the adequacy of regulations), an efficiency frame (emphasizing precision and benefits), a risks and uncertainty frame (emphasizing unknown outcomes), an animal welfare frame (emphasizing benefits for animals) or an animal dignity frame (considering the inherent value of animals). Animals were often featured as the object of regulations in FAQs, and questions about animals were linked to animal welfare regulations. The public were represented using a variety of terms (public, consumer) and pronouns (I, we). Some FAQs described differences between technology terms (gene editing, genetic modification) and categorized technologies as either well-established or novel. This framing of the technology may not respond to actual public concerns on the topic. Organizations seeking to use FAQs as a public engagement tool might consider including multiple viewpoints and actual questions people have about genetic engineering.

A Novel, Deep Learning-Based, Automatic Photometric Analysis Software for Breast Aesthetic Scoring.

Background Breast aesthetics evaluation often relies on subjective assessments, leading to the need for objective, automated tools. We developed the Seoul Breast Esthetic Scoring Tool (S-BEST), a photometric analysis software that utilizes a DenseNet-264 deep learning model to automatically evaluate breast landmarks and asymmetry indices. Methods S-BEST was trained on a dataset of frontal breast photographs annotated with 30 specific landmarks, divided into an 80-20 training-validation split. The software requires the distances of sternal notch to nipple or nipple-to-nipple as input and performs image preprocessing steps, including ratio correction and 8-bit normalization. Breast asymmetry indices and centimeter-based measurements are provided as the output. The accuracy of S-BEST was validated using a paired t -test and Bland-Altman plots, comparing its measurements to those obtained from physical examinations of 100 females diagnosed with breast cancer. Results S-BEST demonstrated high accuracy in automatic landmark localization, with most distances showing no statistically significant difference compared with physical measurements. However, the nipple to inframammary fold distance showed a significant bias, with a coefficient of determination ranging from 0.3787 to 0.4234 for the left and right sides, respectively. Conclusion S-BEST provides a fast, reliable, and automated approach for breast aesthetic evaluation based on 2D frontal photographs. While limited by its inability to capture volumetric attributes or multiple viewpoints, it serves as an accessible tool for both clinical and research applications.