Young Humans Make Change, Young Users Click: Creating Youth-Centered Networked Social Movements

From the urbanists' perspective, the everyday experience of young people, as an underrepresented group in the design of public spaces, includes tactics they use to challenge the strategies which rule over urban spaces. In this regard, youth led social movements are a set of collective tactics which groups of young people use to resist power structures. Social informational streams have revolutionized the way youth organize and mobilize for social movements throughout the world, especially in urban areas. However, just like public spaces, these algorithm based platforms have been developed with a great power imbalance between the developers and users which results in the creation of non inclusive social informational streams for young activists. Social activism grows agency and confidence in youth which is critical to their development. This paper employs a youth centric lens, which is used in designing public spaces, for designing algorithmic spaces that can improve bottom up youth led movements. By reviewing the structure of these spaces and how young people interact with these structures in the different cultural contexts of Iran and the US, we propose a humanistic approach to designing social informational streams which can enhance youth activism

Investigating the Effectiveness of Semantic Tagging in Sense Disambiguation of Specialized Homographs from the perspective of F-Measure in Retrieving scientific texts

The aim of this study was to explain the application of text corpus tagging method in Sense disambiguation from specialized homographs and increasing the retrieval F-Measure of scientific texts containing such homographs.This is an experimental study. Specialized homographs were identified by direct observation and morphological analysis of the word. The research sample consisted of 442 scientific articles of two groups of experimental group and control group. The control group had 221 full-text articles without tags and the experimental group had same 221 tagged articles, which were tested in the information retrieval system to measure the effectiveness of tagging in word sense disambiguation from specialized homographs.The level of significance of the Wilcoxon signed-rank test showed that the F-Measure of retrieval results of specialized homographs after using the tagged specialized text corpus in the information retrieval system is significantly different than before. Examination of negative and positive rankings showed that the F-Measure of the results after using the tagged specialized text corpus has increased significantly and has reached its maximum level of 1.The findings of the present study showed that there is not necessarily an inverse relationship between recall and precision, and the two can reach their maximum level of 1. The better efficiency of the retrieval system using this approach is due to the empowerment of the retrieval system in distinguishing between specialized homographs and identifying their semantic roles by using semantic tags as training data that were considered in the test and training set. Embedding the training set in the structure of the retrieval system provides additional information to serve the retrieval system to distinguish between the various meanings of specialized homographs. This tool is one of the elements that causes the optimal quality of retrieval and leads the information retrieval system from word-driven retrieval to content-driven retrieval when retrieving texts containing specialized homographs

Stochastic Vision Transformers with Wasserstein Distance-Aware Attention

Self-supervised learning is one of the most promising approaches to acquiring knowledge from limited labeled data. Despite the substantial advancements made in recent years, self-supervised models have posed a challenge to practitioners, as they do not readily provide insight into the model's confidence and uncertainty. Tackling this issue is no simple feat, primarily due to the complexity involved in implementing techniques that can make use of the latent representations learned during pre-training without relying on explicit labels. Motivated by this, we introduce a new stochastic vision transformer that integrates uncertainty and distance awareness into self-supervised learning (SSL) pipelines. Instead of the conventional deterministic vector embedding, our novel stochastic vision transformer encodes image patches into elliptical Gaussian distributional embeddings. Notably, the attention matrices of these stochastic representational embeddings are computed using Wasserstein distance-based attention, effectively capitalizing on the distributional nature of these embeddings. Additionally, we propose a regularization term based on Wasserstein distance for both pre-training and fine-tuning processes, thereby incorporating distance awareness into latent representations. We perform extensive experiments across different tasks such as in-distribution generalization, out-of-distribution detection, dataset corruption, semi-supervised settings, and transfer learning to other datasets and tasks. Our proposed method achieves superior accuracy and calibration, surpassing the self-supervised baseline in a wide range of experiments on a variety of datasets

Análisis numérico de diferentes geometrías en el análisis dinámico en la plataforma de gravedad.

On Gravity platform Dynamic Response is a support structure held in place by gravity. Given that the gravity platforms are supportedby the sea bed but not attached to the ground, the motion of them is known as a rocking fluctuation. During the fluctuations, theplatform maybe overturned if the angle is large. In this study, using Ansys Aqwa hydrodynamic software and analytical methods withregard to the performance, the dynamic interaction of platform’s geometry on hydrodynamic forces have been simulated. Theobjective of this study was to analyze the hydrodynamic parameters of the sea and rocking fluctuations of gravity platforms under theimpact of regular wave’s moment considering the soil mechanics and hydrodynamic features of the structure. In order to achievethe objective the hydrodynamic forces using numerical simulations and analytical methods for one column and three hollow columnsplatforms were analyzed. Finally, responses of the platform to irregular waves were studied using numerical simulation. The resultsshowed that with the increasing of the depth, the impact of wave’s force and moment on the base of platform are reduced throughexponential relationship. The reductions are due to the effective depth that is equal to half the wave length. The results suggestthat the response of the rocking motion of gravity platform shows significant changes in relation to height and wavelength. Based onthe curves fitted to the data of the fluctuation angle, sustainability of the platform in the rocking motion can be thoroughly andcompletely investigated