Perspective Of Representation Research Articles

Developing a Multiscale Neural Connectivity Knowledgebase of the Autonomic Nervous System.

The Stimulating Peripheral Activity to Relieve Conditions (SPARC) program is a U.S. National Institutes of Health (NIH) funded effort to enhance our understanding of the neural circuitry responsible for visceral control. SPARC's mission is to identify, extract, and compile our overall existing knowledge and understanding of the autonomic nervous system (ANS) connectivity between the central nervous system and end organs. A major goal of SPARC is to use this knowledge to promote the development of the next generation of neuromodulation devices and bioelectronic medicine for nervous system diseases. As part of the SPARC program, we have been developing SCKAN, a dynamic knowledge base of ANS connectivity that contains information about the origins, terminations, and routing of ANS projections. The distillation of SPARC's connectivity knowledge into this knowledge base involves a rigorous curation process to capture connectivity information provided by experts, published literature, textbooks, and SPARC scientific data. SCKAN is used to automatically generate anatomical and functional connectivity maps on the SPARC portal. In this article, we present the design and functionality of SCKAN, including the detailed knowledge engineering process developed to populate the resource with high quality and accurate data. We discuss the process from both the perspective of SCKAN's ontological representation as well as its practical applications in developing information systems. We share our techniques, strategies, tools and insights for developing a practical knowledgebase of ANS connectivity that supports continual enhancement.

Cinematic Language under the Female Gaze: A Case Study of Li Yu

Abstract: This paper aims to discover the concept of the female gaze in the movie Lost in Beijing by Li Yu. The female gaze is a film theory that is in opposition to the male gaze, which is a way of viewing women as sexual beings and not as complex people. This paper posits that Li Yu uses the female gaze as a post-modernist technique to focus on the emotional and psychological aspects of the female characters, thus overturning the established Patriarchal gender norms and bringing to the fore the issues of gender inequality in contemporary Chinese society. Certain filming approaches, including those that include close ups and reflective shots, affect the experience of the film's main subject, who are women. The research also reviews the variance between the 'male gaze' and the 'female gaze' in movies, pointing out that the former is much more forthright and authentic in its portrayal of women. Lastly, the paper considers the further developments of the concept of the female gaze and possibilities to transform the film industry from the perspective of the female representation.

A Comparative Analysis of Post-Modern Planning: A Case Study of Mumbai and Rosario

This paper compares the Kanjur Marg Project in Mumbai and the 26 Local Strategies: A Plan in Rosario from a globalization perspective. Despite both projects reflecting postmodernist planning characteristics, they highlight the similarities and differences in their urban planning approaches. The differences in resident participation in the two cities reflect their unique social, political, and global contexts. The Kanjur Marg Project in Mumbai combines collaborative and radical planning through deep Metropolitan resident participation. At the same time, the 26 Local Strategies: A Plan in Rosario represents a more typical collaborative planning approach through participatory workshops. This paper analyses how these planning approaches shape urban development trajectories and to what extent they achieve social justice from the perspectives of representation, redistribution, and recognition in the context of globalization. The study suggests that these cases demonstrate the multiple challenges of urban development and social justice in the context of globalization and call for further exploration of how to achieve more inclusive and just urban planning in the process of globalization

A Comparative Analysis of Post-Modern Planning: A Case Study of Mumbai and Rosario

This paper compares the Kanjur Marg Project in Mumbai and the 26 Local Strategies: A Plan in Rosario from a globalization perspective. Despite both projects reflecting postmodernist planning characteristics, they highlight the similarities and differences in their urban planning approaches. The differences in resident participation in the two cities reflect their unique social, political, and global contexts. The Kanjur Marg Project in Mumbai combines collaborative and radical planning through deep Metropolitan resident participation. At the same time, the 26 Local Strategies: A Plan in Rosario represents a more typical collaborative planning approach through participatory workshops. This paper analyses how these planning approaches shape urban development trajectories and to what extent they achieve social justice from the perspectives of representation, redistribution, and recognition in the context of globalization. The study suggests that these cases demonstrate the multiple challenges of urban development and social justice in the context of globalization and call for further exploration of how to achieve more inclusive and just urban planning in the process of globalization

Dual Contrastive Learning for Cross-Domain Named Entity Recognition

Benefiting many information retrieval applications, named entity recognition (NER) has shown impressive progress. Recently, there has been a growing trend to decompose complex NER tasks into two subtasks (e.g., entity span detection (ESD) and entity type classification (ETC), to achieve better performance. Despite the remarkable success, from the perspective of representation, existing methods do not explicitly distinguish non-entities and entities, which may lead to ESD errors. Meanwhile, they do not explicitly distinguish entities with different entity types, which may lead to entity type misclassification. As such, the limited representation abilities may challenge some competitive NER methods, leading to unsatisfactory performance, especially in the low-resource setting (e.g., cross-domain NER). In light of these challenges, we propose to utilize contrastive learning to refine the original chaotic representations and learn the generalized representations for cross-domain NER. In particular, this article proposes a dual contrastive learning model (Dual-CL), which respectively utilizes a token-level contrastive learning module and a sentence-level contrastive learning module to enhance ESD, ETC for cross-domain NER. Empirical results on 10 domain pairs under two different settings show that Dual-CL achieves better performances than compared baselines in terms of several standard metrics. Moreover, we conduct detailed analyses to are presented to better understand each component’s effectiveness.

“Inviting people into our experience in a powerful way”: Indigenous Representation in the Television Series Burden of Truth and Midnattssol

Abstract: Introducing diversity into the white-dominated media business is part of mainstreaming social justice movements. This article addresses Indigenous themes’ and talents’ inclusion in two television series by mainstream production companies from the perspectives of organic representation, inclusivity, and justice. The analysis focuses on Canadian legal drama Burden of Truth (2018–2021) and French-Swedish Nordic Noir Midnattssol ( Midnight Sun , 2016). It considers the participation of Indigenous talents and their realistic address of social concerns and argues that both series work within the constraints of their political economies while offering modes for representation that demonstrate possibilities for creating inclusive and socially impactful, yet entertaining, productions.

Revisiting Hindu Marriage Norms: Unveiling Women’s Agency in Ancient India

This article extensively explores marriage norms in ancient India, focusing on women's agency. It begins by dissecting the concept of marriage and its variations in ancient India and sheds light on its significance from women's viewpoints. It scrutinises the roles of women within the institution, including debates surrounding the age of marriage, the qualities sought in brides, and the complexities of partner selection including the prohibited degrees of marriage. The paper delves into her roles in marriage rituals as well as post-marital positions. Contentious issues like divorce and remarriage of women have also been touched. Overall, this article aims to uncover obscure aspects of women's autonomy within marriage, analysing their roles and representations across all facets. By examining evolving Hindu marriage norms throughout the Vedic, Puranic and Smriti periods, it emphasizes the need for a refined understanding of women's agency. The paper seeks to contribute to a comprehensive understanding of marriage in ancient India, particularly from the perspective of women's representations, urging readers to reconsider conventional narratives. Journal of the Asiatic Society of Bangladesh (Hum.), Vol. 69(1), 2024, pp. 1-32

Face Anti-Spoofing with Unknown Attacks: A Comprehensive Feature Extraction and Representation Perspective

Face Anti-Spoofing with Unknown Attacks: A Comprehensive Feature Extraction and Representation Perspective

Hashtagging for Inclusion: Complex Identities in Singaporean Gay Men’s Social Representation on Instagram

Beyond indexing content and creating networks, hashtags can also convey social meanings. From the perspective of social representation, this article investigates how gay men in Singapore use various hashtags to represent their complex identities and create a shared meaning of being gay in Singapore. Through a textual analysis of identity-related posts generated by gay Instagram users in Singapore, we identified two patterns of using gay-related hashtags: habitual and contextual. Both patterns rely on and demonstrate the identity complexity of gay users. The patterns suggest the users’ identity management online while engendering different forms of social representation for Singaporean gay men. By using non-gay hashtags and juxtaposing them with gay ones, the users could disseminate outreach information, establish social connections, and improve the digital inclusion of their group. We also found unusual exclusions of gay hashtags, suggesting the potential conflict between gayness and some traditional values/roles in Singapore.

High school students’ preconceptions about the concept of climate change considered from the perspective of visual representation

Preconceptions are an essential foundation for students, serving as a basis for more effective learning. In the context of climate change concepts, many students harbor misconceptions. One method to uncover students’ preconceptions is through the use of visual representations. Visual representations can elucidate students’ understanding of abstract and complex concepts. This study aims to examine and analyze the extent of high school students’ comprehension of climate change. The research employs a descriptive qualitative approach, with a population and sample comprising 63 tenth-grade science students from a high school in Indonesia. Data collection techniques included observation and interviews, with semi-structured interviews being utilized in this study. The results reveal that students have varied understandings of the concept of climate change, with many exhibiting misconceptions. The study identifies three categories of climate change concepts: (1) correct concepts of climate change, representing 37%; (2) climate change concepts based on objects, as depicted in the visualizations provided by the respondents; and (3) incorrect concepts of climate change, representing 63%. Based on empirical evidence, the students’ preconceptions of climate change are predominantly at the macroscopic level.

Spatial–Spectral Total Variation-Regularized Low-Rank Tensor Representation for Hyperspectral Anomaly Detection

Hyperspectral anomaly detection is a vital aspect of remote sensing as it focuses on identifying pixels with distinct spectral–spatial properties in comparison to their background representations. However, existing methods for anomaly detection in HSIs often overlook the spatial correlation between pixels by converting the three-dimensional tensor data into its folded form of independent signatures, which may lead to insufficient detection performance. To address this limitation, we develop an anomaly detection algorithm from a tensor representation perspective, which begins by separating the observed hyperspectral image into background and anomaly cubes. We leverage the tensor nuclear norm (TNN) to capture the inherent low-rank structure of background cube globally. This allows us to effectively model and represent the background information. To further improve the detection performance, we introduce spatial–spectral total variation (SSTV) for effectively promoting piecewise smoothness of the background tensor, aiding in the identification of anomalies. Additionally, we incorporate RX-derived attention weights-guided [Formula: see text] norm. This encourages group sparsity of anomalous pixels, improving the precision of anomaly detection. To solve our proposed method, we employ the alternating direction method of multipliers (ADMM), ensuring guaranteed convergence and efficient computation. Through experiments on different kinds of hyperspectral real datasets, we have demonstrated that our method surpasses several state-of-the-art detectors.

Exploring social cognition in an international context: insights from the social representations perspective on legitimacy among French entrepreneurs

ABSTRACT In the field of international entrepreneurship, there are increasing calls for the study of cognition in its social context. In this regard, this article draws on social representations theory to explore and better understand the cognition of entrepreneurs. The objective of the present study is to explore the social representation of legitimacy among different social groups and show how these collective images vary depending on the context in which entrepreneurs operate. By applying social representations theory to data gathered from a sample of 150 French entrepreneurs, we construct a framework that elucidates social development and the changes that influence entrepreneurs’ decision-making. In addition, this article reveals a new avenue of study in relation to legitimacy from a collective perspective.

Degressively proportional representation in the European Parliament: European Union law versus reality

ABSTRACT As the European Parliament is the first transnational representative body based on the Member States representation, the apportionment of seats among the European Union Member States may be a relevant issue. This article is conceived as an idiographic case study and presents an analysis of the composition of the European Parliament in the territorial representation perspective. According to the 2007 Lisbon Treaty, there should be degressively proportional representation in the European Parliament. Following that existing EU legislation implies an uneven representation of citizens in the European Parliament across the EU Member States, this study pursues the following two goals. Firstly, it seeks to quantify malapportionment (the degressive proportionality principle), i.e. distortion of the proportional representation of the Member States (malapportionment) and under-/over-representation of individual Member States, in European elections since 1979 when the direct elections of MEPs were introduced. Secondly, it aims to answer whether there has in fact been a degressively proportional representation in the European Parliament. This article concludes that malapportionment has stabilized at fourteen to fifteen per cent of the total seats since the 2004 European election, but there has been no degressively proportional representation in the European Parliament since 2004.

Representations of Post-Industrial Shanghai

This article explores how vernacular aesthetics have been re-appropriated from pictorial to modern documentary photography over the past century to instigate a modern collective imagination of the industrial disintegration in the Chinese urban milieu. Within the scope of a discursive visual process, Jean Philippe Gauvrit (b.1963) documents the departure of the industrial urban society in his photo-essay Shanghai in JP Gauvrit (2008). The paper claims that Gauvrit’s documentary photography can be understood as a visual critical discourse of several representational perspectives of time that render visible anachronistic and new social structures that come into being: between utopias of the past and visions of the future in an alternative chronotopic ‘present’ cartography. Drawing on Bakhtin’s (1981) conception of chronotope, in this study, the sublime industrial comes to be represented as an intelligible reconfiguration of linear and cyclical time. By linking that socio-economic reality of that time with a collective consciousness, documentary photography can serve as a chronotope that reveals both the tension and the assimilation relating to the historical myths that lie between the fall of an industrial mode of production and the birth of a post-industrial cultural city in an era of de-industrialization.

A Survey on Monocular Re-Localization: From the Perspective of Scene Map Representation

A Survey on Monocular Re-Localization: From the Perspective of Scene Map Representation

Overview of image-based 3D reconstruction technology

Three-dimensional (3D) reconstruction technology is the key technology to establish and express the objective world by using computer, and it is widely used in real 3D, automatic driving, aerospace, navigation and industrial robot applications. According to different principles, it is mainly divided into methods based on traditional multi-view geometry and methods based on deep learning. This paper introduces the above methods from the perspective of three-dimensional space representation. The feature extraction and stereo matching theory of traditional 3D reconstruction methods are the theoretical basis of 3D reconstruction methods based on deep learning, so the paper focuses on them. With the development of traditional 3D reconstruction methods and the development of deep learning related theories, the explicit deep learning 3D reconstruction method represented by MVSNet and the implicit 3D reconstruction method represented by NeRF have been gradually developed. At the same time, the dataset and evaluation indicators for 3D reconstruction were introduced. Finally, a summary of image based 3D reconstruction was provided.

Selected Methods of Feature Selection - Medical Case Study

The research work aimed to analyse and compare five different feature selection methods belonging to filter and wrapper approaches. The methods were evaluated taking into account the knowledge discovery and knowledge representation perspectives. The Gradient Boosting classifier was used as a benchmark model due to its performance and flexibility. Extensive tests were conducted on the Wisconsin Breast Cancer Diagnostic dataset and indicated cases of enhanced prediction for the reduced set of features.

젊은 세대의 정치적 대표성의 관점에서 바라본 공직선거법과 정당법 개정의 한계와 개선방안

Recently amended legislation related to political participation has a positive aspect in that it has legally and institutionally expanded the political participation of the young generation, including the youth. however, there is a limit to the fact that the political party law still stipulates the grounds for party membership and activities that can embody youth's political responsiveness. In other words, Article 22, Paragraph 1 of the Political Party Act sets an age limit of “16 years of age or older” as a condition for joining a political party. As mentioned above, this has a positive aspect in that the existing voting age was lowered to 16 through revision. however, there is a limitation in restricting party membership and activities by stipulating membership in political parties in the Political Party Act and preventing youth under the age of 16 from becoming party members.
 And in the case of deposits, the youth who have not achieved economic independence are actually restricted in exercising their right to hold public office, which has lowered the age of eligibility for election. Ultimately, follow-up legislative improvements are needed, such as setting the age for joining a political party by the party's voluntary choice, not a regulation in the Political Party Act, or abolishing the age for joining a party, and abolishing the deposit system that restricts the exercise of the right to hold public office by the younger generation.
 Therefore, from the perspective of democracy and generational equality, this paper emphasizes that improvement should be made in the direction of expanding 'representation' by analyzing not only the expansion of the electorate but also the legal and institutional factors that restrict the right to be elected. In order to achieve the purpose of the study, after analyzing the limitations of the recently revised public official election law, Article 56, Paragraph 1 of the deposit system and the political party membership age regulation of Article 22, Paragraph 1 of the Political Party Act, we propose ways to improve them.

Model of cognitive activity of the human brain based on the mathematical apparatus of quantum mechanics

Describing the transmission and processing of information by an individual is a fundamental issue in modern cognitive science. Previously, unique scientific models for information transfer between individuals [1], as well as models for cognitive activity [2], were developed. However, numerous presented models lack scalability and formalization, hindering their ability to provide a comprehensive explanation for information transfer processes and their distortion due to interaction with the external communicative environment. One aspect of human cognitive activity is that individuals think not based on a code, as a computer does, but through the interaction of various mental images. Despite the fact that these images have a specific material foundation in the form of electrical and chemical activity in the human brain, describing them using conventional mathematical models presents several difficulties [3]. Therefore, this paper suggests novel techniques for describing information images/representations’ functioning, which simulate an individual’s cognitive activity. These methods rely on the mathematical models of self-oscillatory and conventional quantum physics (including potential wells and virtual particles conventionally used in the physical domain) for characterizing basic interactions [4]. The authors adopt a phenomenological perspective and do not regard cognitive systems as quantum. The aim of this study ject is to establish a model for cognitive function in the human brain using the mathematical principles of self-oscillating quantum mechanics from the perspective of information imaging and representation. Methods. The theory proposes [5] that information images/representations (IR) share characteristic properties with virtual Feymann particles and other elementary particles. The human mind is presented as a one-dimensional potential well with finite walls of varying sizes and an internal potential barrier that simulates the boundary between consciousness and subconsciousness. The authors have applied parametrization based on this theory. As a result, we propose the foundations of the mathematical apparatus based on classical quantum mechanics, followed by the mathematical apparatus of self-oscillating quantum mechanics. The latter, though little known, may allow to predict certain cognitive functions of the human brain by modifying and applying it to non-quantum settings. An equation is derived for the state function of the information image of an individual engaging in cognitive activity. Primary calculations were conducted on the state functions of information images using a computer model. The movement patterns of the information image within and outside were then deduced.

Supervised adaptive similarity consistent latent representation hashing

Cross-modal hashing has attracted significant attention in multimedia data similarity given its appealing computational cost and retrieval performance. Supervised hashing benefits from the auxiliary learning of a similarity matrix, which is usually predefined by inner product features or category labels. However, a predefined similarity matrix fails to reflect the real similarity relationship between image-text pairs. In addition, existing methods fix the weights to a value or update them by introducing sensitive dataset-related hyper-parameters. To overcome these problems, we propose a method to perform supervised adaptive similarity consistent latent representation hashing (SCLRH) that adaptively learns the similarity matrix during hashing learning. In SCLRH, we assume that multimodal data are observed and reconstructed from different perspectives of a common consistent latent representation. Instead of using a predefined similarity matrix, SCLRH adaptively learns this matrix to reflect the underlying manifold structure and describes the fine-grained similarity between consistent latent representations. In addition, SCLRH introduces a self-weighted learning strategy to update the weights based on the contributions of different modalities without involving additional hyper-parameters. Experimental results on three benchmark datasets demonstrate the superiority of the proposed SCLRH for cross-modal retrieval.