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Academic contribution to collective building of the city – An experience in the countryside of Ceará – Brazil
No full textThe appropriation of space is directly linked to the sense of belonging and identity of the place and with place. When the population participates in the planning process, the way of appropriation of the public space is differentiated and much more effective. Based on this assumption, the research group Collaborative Urbanism – UrbColab, linked to the Research Center in Architecture, City and Technology – NuPACT, aims to foster discussion about aspects of daily life that influence the collective construction of the city, more specifically in the small and medium-sized cities of Ceará (Brazil), promoting a dialogical relationship between academia, society and the public power. By working horizontally and inclusively, we make room for the demands that appear and that is in line with the group’s proposal. Among them, as a partial result, we are consolidating three work fronts that emerged as demands: technical assistance in the preparation of the Carnaubal Master Plan; creation of proposals for the revision of the Sobral Master Plan and; training cycle for the preparation of Participatory Master Plans. This article aims to show the importance of academic engagement in the discussions of the city as a way to disseminate knowledge and be able to act effectively in the construction of more dignified and inclusive cities
A Deep Learning Approach for Urban Block: Automated Extraction Tool for Urban Forms
No full textIncreasing access to geographic data and mapping technologies has pushed urban morphology research toward more quantitative and data-driven approaches. At the same time, the unprecedented rapid change in the urban form has prompted a growing number of research to capture, analyze, and understand the phenomenon in recent years. However, a thorough, systematic approach to evaluating and comparing urban forms in this setting is yet to be developed. The aim of this study is to build a comprehensive approach to defining urban form indicators by developing a simplified yet representative classification of the urban form. Notably, urban block as a constitutional feature of urban form is evaluated in relation to numerical indices. The applied methodology comprises the detection and classification of urban form using a deep convolutional neural network. The study attempts to use automated methods to address the gap in urban form classification and characterization. The methodological process encompasses a non-local classification of urban form, followed by an examination of the identified features of the urban block. The preliminary outcome of this study consists of an in-depth analysis of urban block indicators in the comparative literature. This will be one of the inputs of the deep learning model to classify urban blocks
Dynamic Place Attachment as Enabler in Redevelopment Programs of Singapore Public Housing Neighborhoods
No full textSingapore is characterized by land scarcity, rapidly changing demographic conditions, and around 80% of its population living in public housing. In the context of massive urban regeneration-induced displacement programs, and particularly ‘Selective En-bloc Scheme’ (SERS), this paper seeks to illuminate the dynamic nature of place attachment in response to change and uncertainty. Informed by the literature review, we propose an original conceptual framework to capture place attachment at displacement, with particular focus on the role of place and time. The framework comprises four interdependent dimensions, namely: socio-spatial network, community ties, engagement/negotiation and continuity/familiarity. A five-week pilot study was conducted in Tanglin Halt neighborhood, currently undergoing its third displacement project. It employed mixed-method research, comprising policy-review, initial spatial mapping and analysis, first-person observations, and 137 surveys and 38 interviews with local residents and visitors. Key-findings highlight the continuous role of built-environment, socio-spatial heart in particular, in construction and re-construction of place attachment over-time, whereby the presence of a socio-ecological system promotes dynamic (rather than stagnant) occurrence of place attachment and adaptation to disruptions. If carefully considered, place attachment can improve relocation processes and enable mobility. Finally, the pilot study informed an ongoing longitudinal study, with refined spatial mapping method
Szybkie randki i spotkania dla rodziców, czyli studenci międzynarodowi opracowują strategię dla BON
No full textIdentification of Melanocytic Skin Lesions Using Deep Learning Methods
No full textDetection of skin cancer at an early stage is a priority in the
fight to reduce mortality. The aim of the paper is to develop a method of
computer aided diagnosis of melanocytic skin lesions through analysis of
dermatoscopic images using deep NN methods. In particular, the goal is to
use the multiple binary CNN model approach. The results obtained are much
better in distinguishing between categories of lesions compared to the model
built on the entire 7-class image database
Objective Hybrid Quality Assessment of Binary Images with the Use of Shallow Neural Networks
No full textThe state-of-the-art image quality assessment methods designed
for binary images are not highly correlated with subjective evaluation results,
therefore one of the efficient methods to improve their performance is
the application of shallow neural networks. In such an approach each elementary
metric is used as the input of the network and the network is trained
with subjective quality scores used as the goal function. The obtained correlation
with subjective scores depends not only on the number of elementary
metrics and their choice but also on the training algorithm and the network’s
structure as presented in the paper
Z wizytą studyjną u południowych sąsiadów – Centrum Tejrezjasza na Uniwersytecie Masaryka w Brnie
No full textLocal Energy Redistribution Units for Space Dimensionality Reduction in Data Classification
No full textIn this paper, we present locally trained 2-input to 2-output neurons
called Local Energy Redistribution Units (LERUs), which enable to
transfer most of the input data energy to the selected output, and when organized
into properly designed networks, allow for the energy accumulation
in lower-indexed elements of output vectors. This property can be used to
reduce the dimensionality of the input data space, resulting in a reduction in
the number of weights and disk space needed to store neural network models.
We test the effectiveness of the proposed approach experimentally in the
task of data classification using the well-known MNIST dataset
Zastosowanie metod radiometrycznych do badania transportu i retencji radionuklidów w matrycach stałych
No full textbrak autoreferatuŹródło BIP (https://politechnikalodzka.ssdip.bip.gov.pl/dyscyplina-nauki-chemiczne-dr-hab/277853_dyscyplina-nauki-chemiczne.html