Conceptualizing In-Text “Kshetra”: Postcolonial Allahabad’s Cultural Geography in Neelum Saran Gour’s Allahabad Aria and Invisible Ink

Literary renditions of cities have always gravitated towards the spatial imagination and its ethical counterpart outside the textual space. This paper explores the multicultural geography of the North Indian city Allahabad (recently renamed Prayagraj) observed through Neelum Saran Gour’s postcolonial narratives Allahabad Aria and Invisible Ink, projecting the narrative alignment of spatial aesthetics and cultural ethics. Interrogating the spatial dimensions of a “narrative world” within narrative theory (Ryan) and its interdisciplinary crossover with cultural geography (Sauer; Mitchell; Anderson et al.), the article seeks to examine Gour’s literary city not simply as an objective homogeneous representation, but as a “kshetra” of spatio-cultural cosmos of lived traditions, memories, experiences and collective attitudes of its people, in the context of E. V. Ramakrishnan’s theoretical reflections. The article proposes new possibilities of adapting the Indian concept “kshetra” to spatial literary studies; its aim is also to suggest a new source of knowledge about the city of Allahabad through a community introspection of “doing culture” in the texts, bringing into view people’s shared experiences, beliefs, religious practices and traditions as offshoots of the postcolonial ethos. The article aims to re-contextualize the city’s longstanding multicultural ethics in the contemporary times of crisis, which may affect a shift in the city’s relevance: from regional concern to large-scale significance within ethnically diverse South Asian countries and beyond.

The Relationship between Ageism and Well-Being as Mediated through COVID-19-Related Experiences and Discourses

Both COVID-19 and ageism can have a negative impact on the well-being of older people. Yet, our knowledge on the links between COVID-19, ageism and well-being is still emerging. The present study aimed to contribute to this knowledge by exploring the lived experiences of older adults during the COVID-19 pandemic. To do so, we analyzed older persons’ subjective experiences and perceptions of ageism arising from COVID-19-related policies and discourses in two country contexts—Austria and Ireland—and the implications of these experiences for personal well-being. Based on the thematic analysis of 27 interviews with older adults, we found that participants perceived and encountered a discriminatory homogeneous representation of older people as a group. Three specific forms of this homogenization, namely stigmatization, paternalism, and scapegoating, were identified as impact on well-being. Moreover, our analysis showed how these forms of ageism challenge both the individual and social identities of older people, revealing older participants’ different attitudes in responding to this challenge. With reference to the international research literature, we discussed the impact of these experiences on the well-being of older people and the possible legal and socio-political implications of our findings.

An Adversarial Attacks Resistance-based Approach to Emotion Recognition from Images using Facial Landmarks

Emotion recognition has become an increasingly important area of research due to the increasing number of CCTV cameras in the past few years. Deep network-based methods have made impressive progress in performing emotion recognition-based tasks, achieving high performance on many datasets and their related competitions such as the ImageNet challenge. However, deep networks are vulnerable to adversarial attacks. Due to their homogeneous representation of knowledge across all images, a small change to the input image made by an adversary might result in a large decrease in the accuracy of the algorithm. By detecting heterogeneous facial landmarks using the machine learning library Dlib we hypothesize we can build robustness to adversarial attacks. The residual neural network (ResNet) model has been used as an example of a deep learning model. While the accuracy achieved by ResNet showed a decrease of up to 22%, our proposed approach has shown strong resistance to an attack and showed only a little (< 0.3%) or no decrease when the attack is launched on the data. Furthermore, the proposed approach has shown considerably less execution time compared to the ResNet model.

An Adversarial Attacks Resistance-based Approach to Emotion Recognition from Images using Facial Landmarks

Emotion recognition has become an increasingly important area of research due to the increasing number of CCTV cameras in the past few years. Deep network-based methods have made impressive progress in performing emotion recognition-based tasks, achieving high performance on many datasets and their related competitions such as the ImageNet challenge. However, deep networks are vulnerable to adversarial attacks. Due to their homogeneous representation of knowledge across all images, a small change to the input image made by an adversary might result in a large decrease in the accuracy of the algorithm. By detecting heterogeneous facial landmarks using the machine learning library Dlib we hypothesize we can build robustness to adversarial attacks. The residual neural network (ResNet) model has been used as an example of a deep learning model. While the accuracy achieved by ResNet showed a decrease of up to 22%, our proposed approach has shown strong resistance to an attack and showed only a little (< 0.3%) or no decrease when the attack is launched on the data. Furthermore, the proposed approach has shown considerably less execution time compared to the ResNet model.

Đổi Mới and the Globalization of Vietnamese Art

Đổi Mới reforms triggered significant changes in the Vietnamese art world, including new institutional spaces, platforms for critical discourse, and growing artistic mobility. However, it is important to question the ways in which the use of Đổi Mới as a blanket indicator of artistic reform has further constructed a homogeneous representation of “Vietnamese contemporary art.” The authors consider the relationship of Đổi Mới to the “globalization” of Vietnamese art with attention to questions of art historiography (the coining of such terms as “post-Đổi Mới Vietnamese art”) and variations in regional developments (positing local art histories against the national narrative).

Confidence-Based Participatory Forest Management

This paper formulates a new strategy for participatory forest management consisting of encouraging public participation as long as it increases empathy among participants. The strategy requires the homogeneous representation of the opinion of a participant (i.e. to determine how they assess a forest plan and identify the best one). Utility assessments are prepared for participants through pair-comparisons between meaningful points in the territory and from value functions based on forest indicators. The best plan is designed by applying combinatorial optimization algorithms to the utility of a participant. The calculating of empathy -of one participant relative to another - is based on the equivalence of their respective utilities when the current forest plan is modified. This involves calculating the opinions that are due to systematic changes in the collective plan for those participants that each participant supposes will affect the utility of the other participants. Calculating empathy also requires knowing the interactions among participants, which have been incorporated through agent-based simulation models. Application of the above methodology has confirmed the association between increases in empathy and convergence of opinions in different scenarios: well and medium-informed participants and with and without interaction among them, which verifies the proposed strategy. In addition, this strategy is easily integrated into available information systems and its outcomes show advantages over current participatory applications.

Predictions of Armour Wire Buckling for a Flexible Pipe Under Compression, Bending and External Pressure Loading

During installation and operation a flexible pipe may be subjected to high compressive forces, high cyclic curvatures and external pressures leading to high reverse end-cap loads. Under such loading conditions, which occur particularly in the touchdown region for deep water applications, the limiting condition for the flexible pipe can be the compressive stability of the tensile armour wires. Two potential instability modes are possible: radial mode (birdcaging) and lateral mode (lateral wire disorganization). Previous work on the subject has established the key factors which influence the onset of each buckling mode [1],[2],[3] and [4]. In order to ensure the feasibility of flexible designs for applications with increasing water depth, it is important to improve the knowledge of the mechanisms which can lead to instability of armour wires and enhance the ability to predict with greater assurance, the particular conditions which increase the risk of wire instability. The focus of this work is the comparison of finite element prediction of radial buckling (birdcaging) with physical testing results under loading states that lead a pipe to birdcaging failure. The numerical model incorporates all tensile armor wires and their interactions with each other and adjacent layers. The outer sheath and reinforcing tape layers are explicitly represented, while the inner layers of the pipe (pressure armour and carcass sheath) are idealized using a homogeneous representation. The model also incorporates the effects of manufacturing pre-tension and hoop strength in the anti-birdcaging tape layers which are critical determinants for the onset of buckling. A key aspect of the method presented is the means by which the loading is applied. Specifically, the modeling handles the simultaneous and controlled application of end rotations, axial compression and radial resistance of the tapes through to the point of tape failure, pipe ovalisation and subsequent radial displacement and buckling of individual wires. In summary, in this paper a solid modeling approach is presented, which is compared with full a scale sample test data, that enables the simulation of a flexible pipe undergoing large combined compression, curvatures and pressure loading.