ICCSA 2022

Producción CientíficaThe process of economic, social, and cultural development leads to relevant changes in urban areas. Urban transformations usually generate a series of public and private real estate compounds which constitute real obstacles to urban walkability. The growing attention towards the sustainable development goals established on a global scale introduced new contents in urban redevelopment policies, aimed at favoring higher levels of accessibility in the consolidated fabric, particularly that of the pedestrian type. In addition, the recent pandemic has recently reassessed the role of pedestrian mobility as a primary way of moving instead of using other means of transport. As a result, urban walkability has moved at the core of the sustainable city paradigm. More precisely, issues related to accessibility and walkability should be considered when addressing the obstacle generated by those sites that can be properly defined ‘urban enclaves’, especially when abandoned or under redevelopment. These conditions may encourage the gradual reopening of these areas for citizens. Within this framework, the Sustainable Urban Mobility Plan (SUMP) can represent a strategic tool for identifying the critical aspects to face for the creation of a new network of pedestrian routes aimed at improving urban walkability. The objective of this study is to define a set of principles and criteria, both tangible and intangible, for calculating the proximity index (PI). The PI may consequently drive urban regeneration projects also through the design of new paths for crossing the enclaves to improve urban permeability and, therefore, the level of walkabilitySardinia Foundation (CUP F74I19001040007

Improving Variabilty Analysis through Scenario-Based Incompatibility Detection

Software Product Line (SPL) developments include Variability Management (VA) as a core activity aiming at minimizing the inherent complexity in commonality and variability manipulation. Particularly, the (automated) analysis of variability models refers to the activities, methods and techniques involved in the definition, design, and instantiation of variabilities modeled during SPL development. Steps of this analysis are defined as a variability analysis process (VA process), which is focused on assisting variability model designers in avoiding anomalies and/or inconsistencies, and minimizing problems when products are implemented and derived. Previously, we have proposed an approach for analyzing variability models through a well-defined VA process (named SeVaTax). This process includes a comprehensive set of scenarios, which allows a designer to detect (and even correct in some cases) different incompatibilities. In this work, we extend SeVaTax by classifying the scenarios according to their dependencies, and by assessing the use of these scenarios. This assessment introduces two experiments to evaluate accuracy and coverage. The former addresses responses when variability models are analyzed, and the latter the completeness of our process with respect to other proposals. Findings show that a more extensive set of scenarios might improve the possibilities of current practices in variability analysis.Fil: Buccella, Agustina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Confluencia; Argentina. Universidad Nacional del Comahue. Facultad de Informatica; ArgentinaFil: Pol'la, Matias Esteban. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Confluencia; Argentina. Universidad Nacional del Comahue. Facultad de Informatica; ArgentinaFil: Cechich, Susana Alejandra. Universidad Nacional del Comahue. Facultad de Informatica; Argentin

Green Infrastructure and Slow Tourism: A Methodological Approach for Mining Heritage Accessibility in the Sulcis-Iglesiente Bioregion (Sardinia, Italy)

In European countries many measures are carried out to improve the disadvantaged conditions and socio-economic marginality of rural areas in comparison with central places. These conditions also affect the quality of travel for visitors and tourists. Therefore, in response to a ‘new’ tourist demand, motivated also by the restrictions following the spread of the COVID-19 virus in recent years, the institutions and the different local actors are working more incisively to improve rural areas. The rural tourism services offer, combined with the Green Infrastructure (GI) project, at different scales—from local to regional—interesting territorial development strategies to achieve the Agenda 2030 objectives. This contribution considers the Sulcis-Iglesiente-Guspinese area, in the Sardinia Region (IT), as a case study. In this area, the landscape context is marked by past mining activity, and the project of a path of historical, cultural, and religious values has proven to be an activator of regenerative processes, in environmental, social, and economic terms. The present study proposes a methodological approach to develop an index (FI—feasibility index) to assess the feasibility of the Stop Places (SPs) project along a horse trail to integrate the current slow mobility of bicycles and pedestrians in the bioregion

From appraisal function to Automatic Valuation Method (AVM). The contribution of International Valuation Standards in modern appraisal methodologies

In the real estate appraisal, as well as for any other scientific discipline, there is a continuous development of knowledge with related theoretical and applicative evolution that takes place primarily on the doctrinal level. The discipline has been object of regulatory and technological improvement aimed at concretizing and defining theoretical principles and methodologies. The functions of value appraisal, formulated in the different procedures that fall within the Market Oriented Approach indicated by the International Valuation Standard, have undergone a process of evolution that has favoured the introduction of Automated Valuation Methods (AVM). This evolution process represents an improvement of the conventional appraisal models that have improved the techniques of data retrieval and data base access and certify the reliability of the models to build efficient evaluation processes and universally recognized. This article aims at reviewing the methodological evolution in relation to the national market approach that the estimation discipline has recorded in recent years by virtue of the drafting and adoption of the International Valuation Standards

A Machine Learning Technique for Detection of Social Media Fake News

publishedVersio

Regenerative tourism: A bibliometric analysis

Purpose: Despite regenerative tourism representing a beacon of hope to fight the problems faced by today's humankind, its multidisciplinary essence and fragmentation hinder the identification of major thematic areas for upcoming researchers. Therefore, the present study aims to systematically review the relevant literature on regenerative tourism. Methods: The literature was revised by adopting a bibliometric protocol. Web of Science and Scopus were employed to access pertinent publications, and Biblioshiny was used to track publication and source evolution and impact, main countries and affiliations' production, authors' relevance, productivity, collaborations, perform content, thematic, and co-citations analyses. Results: The literature on regenerative tourism has recently grown, fostered by rising interest due to the COVID-19 crisis. Attention in the field is still limited to a few main players, requiring an expansion in geographic and academic discipline terms. Thematic areas and their level of development were identified, assessing some relevant topics as fairly unexplored, especially concerning mindset change. Implications: This study offers inferences for future researchers and practitioners, employing literature summarizing, main sources and author identification, as well as gap detection, limiting its results to dual database record retrieval, as well as limited scope or search

Data driven spatio-temporal analysis of e-cargo bike network in Lisbon and its expansion: The Yoob case study

The adoption of more environmentally friendly and sustainable fleets for last-mile parcel delivery within large urban centers has been on the rise. Cargo bikes have been the most common alternative. The implementation of this type of fleet has proven to bring benefits, but has evidenced some limitations. The infrastructure network, which supports urban logistics, had to adapt to respond to the requirements of this new type of fleet. The implementation of micro-hubs and nano-hubs was the solution. Our study has two main objectives. The first objective is to perform a spatiotemporal characterization of fleet behavior, by conducting a case study where we explored the data from YOOB (a last mile delivery logistics start-up that operates in the Lisbon area and outskirts) e-cargo bike fleet. And the second is to identify potential expansion locations to the establishment of new hubs. The work procedures followed the CRIPS-DM methodology and the collected data was based on a 4-month period (January to April 2022). By adopting data science and machine learning techniques, five types of performances of YOOB fleet were identified, with variations in distances traveled, times, volumes transported and speeds. In the perspective of expanding YOOB's e-cargo bike network, three new locations in Lisbon were signaled for potential new hub installation.A adoção de frotas mais ecológicas e sustentáveis para a distribuição das encomendas na última milha dentro dos grandes centros urbanos tem vindo a crescer. As bicicletas de carga têm sido a alternativa mais comum. A implementação deste tipo de frotas, demonstrou trazer benefícios, mas evidenciou algumas limitações. A rede de infraestruturas, que serve de suporte á logística urbana, teve de se adaptar para poder responder às necessidades deste novo tipo de frotas. A implementação de microhubs e nano-hubs foram a alternativa. O nosso estudo tem dois objetivos principais. O primeiro objetivo é o de fazer uma caracterização espácio temporal dos comportamentos da frota, através de um estudo de caso onde efetuámos a exploração dos dados da frota de e-cargo bike da YOOB (start-up logística de entregas na última milha que atua na área de Lisboa e na periferia). E o segundo consiste em identificar potenciais locais de expansão para a instalação de novos hubs no mesmo estudo de caso. Nos processos de trabalho foi seguida a metodologia CRISP-DM e os dados recolhidos foram referentes a um período de 4 meses (Janeiro a Abril de 2022). Com recurso a técnicas de ciência dos dados e aprendizagem automática, foram identificados cinco tipos de desempenhos da frota da YOOB, com variações em distâncias percorridas, tempos efetuados, volumes transportados e velocidades praticadas. Numa perspetiva de expansão da rede de e-cargo bike da YOOB, forma identificados três novos locais na cidade de Lisboa para a instalação potencial de novos hubs

Multimodal Emotion Recognition on RAVDESS Dataset Using Transfer Learning

Emotion Recognition is attracting the attention of the research community due to the multiple areas where it can be applied, such as in healthcare or in road safety systems. In this paper, we propose a multimodal emotion recognition system that relies on speech and facial information. For the speech-based modality, we evaluated several transfer-learning techniques, more specifically, embedding extraction and Fine-Tuning. The best accuracy results were achieved when we fine-tuned the CNN-14 of the PANNs framework, confirming that the training was more robust when it did not start from scratch and the tasks were similar. Regarding the facial emotion recognizers, we propose a framework that consists of a pre-trained Spatial Transformer Network on saliency maps and facial images followed by a bi-LSTM with an attention mechanism. The error analysis reported that the frame-based systems could present some problems when they were used directly to solve a videobased task despite the domain adaptation, which opens a new line of research to discover new ways to correct this mismatch and take advantage of the embedded knowledge of these pre-trained models. Finally, from the combination of these two modalities with a late fusion strategy, we achieved 80.08% accuracy on the RAVDESS dataset on a subject-wise 5-CV evaluation, classifying eight emotions. The results revealed that these modalities carry relevant information to detect users’ emotional state and their combination enables improvement of system performance

Sustainable Cities: A Reflection on Potentialities and Limits based on Existing Eco-Districts in Europe

The need for more sustainable cities has become a primary objective of urban strategies. The urgency for a radical transition towards sustainability in a long term-vision has brought with it several new concepts, such as smart urbanism, and models, such as smart city, eco-city, sustainable neighborhood, eco-district, etc. While these terms are fascinating and visionary, they often lack a clear definition both in terms of theoretical insight and empirical evidence. In this light, this contribution aims at defining a conceptual framework through which to further substantiate the blurred concept of eco-district and sustainable neighborhood. It does so by reviewing the concepts of smart urbanism and sustainable neighborhood/eco-districts in the literature, including also references to other well-known sustainability-oriented models of urban development. It then explores whether several indicators, emerging from the analysis of exemplary case studies of sustainable neighborhoods in Europe, can be used to clearly identify the characteristics of a sustainable approach at the district scale. The analysis, built on a review of existing literature, allows for both the clarification of several issues related to these fields of inquiry, as well as for the identification of the potential bridges to link these issues