A New Geospatial Model Integrating a Fuzzy Rule-Based System in a GIS Platform to Partition a Complex Urban System in Homogeneous Urban Contexts

Here, we present a new unsupervised method aimed at obtaining a partition of a complex urbansysteminhomogenousurbanareas,calledurbancontexts.Ourmodelintegratesspatialanalysis processes and a fuzzy rule-based system applied to manage the knowledge of domain experts; it is implemented using a GIS platform. The area of study is initially partitioned in microzones, homogeneous portions of the urban system, which are the atomic reference elements for the census data. With the contribution of domain experts, we identify the physical, morphological, environmental, and socio-economic indicators needed to identify synthetic characteristics of urban contexts and create the fuzzy rule set necessary for determining the type of urban context. We implement the set of spatial analysis processes required to calculate the indicators for the microzones and apply a Mamdani fuzzy rule system to classify the microzones. Finally, the partition of the area of study in urban contexts is obtained by dissolving continuous microzones belonging to the same type of urban context. Tests are performed on the Municipality of Pozzuoli (Naples, Italy); the reliability of the out model is measured by comparing the results with the ones obtained through a detailed analysis

Fuzzy-Based Spatiotemporal Hot Spot Intensity and Propagation—An Application in Crime Analysis

Cluster-based hot spot detection is applied in many disciplines to analyze the locations, concentrations, and evolution over time for a phenomenon occurring in an area of study. The hot spots consist of areas within which the phenomenon is most present; by detecting and monitoring the presence of hot spots in different time steps, it is possible to study their evolution over time. One of the most prominent problems in hot spot analysis occurs when measuring the intensity of a phenomenon in terms of the presence and impact on an area of study and evaluating its evolution over time. In this research, we propose a hot spot analysis method based on a fuzzy cluster hot spot detection algorithm, which allows us to measure the incidence of hot spots in the area of study. We analyze its variation over time, and in order to evaluate its reliability we use a well-known fuzzy entropy measure that was recently applied to measure the reliability of hot spots by executing fuzzy clustering algorithms. We apply this method in crime analysis of the urban area of the City of London, using a dataset of criminal events that have occurred since 2011, published by the City of London Police. The obtained results show a decrease in the frequency of all types of criminal events over the entire area of study in recent years

A GIS-Based Fuzzy Multiclassification Framework Applied for Spatiotemporal Analysis of Phenomena in Urban Contexts

In this research, we propose a GIS-based framework implementing a fuzzy-based document classification method aimed at classifying urban areas by the type of criticality inherent or specific problems highlighted by citizens. The urban study area is divided into subzones; for each subzone, the reports of citizens relating to specific criticalities are analyzed and documents are created, and collected by topic and by temporal extension. The framework implements a model applied to the multiclassification of the documents in which the topic to be analyzed is divided into categories and a dictionary of terms connected to each category is built to measure the relevance of the category in the document. The framework produces, for each time frame, thematic maps of the relevance of a category in a time frame in which a subzone of the study area is classified based on the classification of the corresponding document. The framework was experimented on to analyze and monitor over time the relevance of disruptions detected by users in entities that make up urban areas, such as: roads, private buildings, public buildings and transport infrastructures, lighting networks, and public green areas. The study area is the city of Naples (Italy), partitioned in ten municipalities. The results of the tests show that the proposed framework can be a support for decision makers in analyzing the relevance of categories into which a topic is partitioned and their evolution over time

A Fuzzy Entropy-Based Thematic Classification Method Aimed at Improving the Reliability of Thematic Maps in GIS Environments

Thematic maps of spatial data are constructed by using standard thematic classification methods that do not allow management of the uncertainty of classification and, consequently, eval uation of the reliability of the resulting thematic map. We propose a novel fuzzy-based thematic classification method applied to construct thematic maps in Geographical Information Systems. An initial fuzzy partition of the domain of the features of the spatial dataset is constructed using triangular fuzzy numbers; our method finds an optimal fuzzy partition evaluating the fuzziness of the fuzzy sets by using a fuzzy entropy measure. An assessment of the reliability of the final thematic map is performed according to the fuzziness of the fuzzy sets. We implement our method on a GIS framework, testing it on various vector and image spatial datasets. The results of these tests confirm that our thematic classification method provide thematic maps with a higher reliability with respect to that obtained through fuzzy partitions constructed by expert users

“Un GIS come strumento di supporto alle decisioni per migliorare la stima OMI degli immobili: analisi di prossimità ai servizi. Sperimentazione su alcuni edifici del comune di Napoli”

Obiettivo della tesi è quello di sperimentare un GIS, come strumento a supporto decisionale che migliori la stima del valore economico di un bene immobiliare effettuata dall’Agenzia del territorio. I valori contenuti nella banca dati delle quotazioni immobiliari dell'Osservatorio del mercato immobiliare dell'Agenzia del territorio: Tale stima è costituita da una valutazione di massima delle quotazioni immobiliari determinati dall’Agenzia effettuata suddividendo il territorio in aree omogenee in termini urbanistici, scocio-economici, ambientali, di presenza di servizi, ecc., le zone OMI. Una zona OMI è inserita in un'unica microzona catastale; l’Agenzia determina le stime dei valori minimo e massimo di una quotazione immobiliare per immobili di una determinata destinazione d’uso inseriti in una zona OMI. Il lavoro di tesi intende migliorare questa valutazione prendendo in considerazione in dettaglio i servizi che insistono nel tessuto urbano in cui è localizzato l’edificio in cui l’immobile è ubicato. Fermo restando, infatti , la considerazione ovvia che le stime dell’Agenzia sono solo di massima e non intendono sostituire la valutazione dettagliata del tecnico professionista, che prende in considerazione tutti gli necessari a valutarne il valore economico (lo stato, il valore storico e posizionale, ecc.), lo strumento GIS che si è sperimentato intende analizzare più a fondo la valutazione della presenza di servizi, valutazione troppo generalizzata e fatta nell’ambito di una zona e non considerando le reali distanza lungo la rete di traffico del servizio dal luogo in cui è georiferito l’edificio. Nel lavoro di tesi è stato sperimentato un processo che permette di valutare degli indicatori di prossimità di una specifica tipologia di servizio dall’edificio; con l’utilizzo della fuzzy logica e l’impiego di fuzzy set è stato possibile valutare un indicatore di sintesi finale di prossimità dei servizi all’edificio, normalizzato nell’intervallo [0,1]. L’approccio fuzzy è necessario in quanto rappresenta il modello più adatto alla valutazione del grado di prossimità di un servizio all’edificio, esprimendo in termini di fuzzy set concetti in linguistici come “vicino”, “ a media distanza” e “lontano”. L’indicatore finale di prossimità è determinato in termini di media pesata dei valori di prossimità dei singoli servizi, considerando la rilevanza di ogni servizio. Questo indicatore è stato impiegato per migliorare la valutazione OMI di un’immobile di una certa destinazione d’uso in modo da tenere conto in maniera più approfondita della presenza di servizi che insistono sul complesso territoriale/urbano in cui è situato l’edificio. Le singole fasi del processo sono state messe a punto utilizzando un insieme di funzionalità evolute messe a disposizione dal GIS, quali l’impiego delle funzioni closet facility di network analysis per la determinazione della distanza dal servizio più vicino lungo la rete di traffico e la realizzazione della geobancadati delle zone OMI e l’accesso e l’interrogazione della banca dati delle valutazioni OMI. Nel processo sono stati assegnati su base deduttiva un insieme di parametri quali la distanza di cut-off di un servizio (ovvero la distanza in metri lungo la rete di traffico del servizio più vicino oltre la quale la prossimità del servizio all’edificio è considerata nulla), e il peso o rilevanza del servizio. L’obiettivo della tesi è stato la sperimentazione del processo; ulteriori raffinamenti potranno condurre a valutazioni ancor più precise dei parametri suddetti. Il lavoro di ricerca potrà in futuro essere ulteriormente sviluppato prendendo in considerazione e acquisendo nella geobancadati tutte le caratteristiche informative intrinseche dell’edificio, quali caratteristiche storiche e architettoniche, caratteristiche strutturali e manutentive, presenza di servizi interni e qualitativi come presenza di impianto ascensore, impianto termoautonomo di riscaldamento, posto auto, vano cortile, ecc.)

A Fuzzy-Based Emotion Detection Method to Classify the Relevance of Pleasant/Unpleasant Emotions Posted by Users in Reviews of Service Facilities

Many sentiment analysis methods have been proposed recently to evaluate, through the Web, the perceptions of users and their satisfaction with the use of products and services; these approaches have been applied in various fields in which it is necessary to evaluate, for example, the degree of appreciation of a product or a service or political orientations or emotional states following an event or the occurrence of a phenomenon. On the other hand, these methods are based on natural language processing models needed to capture information hidden in comments, which generally require a high computational cost which can affect their performance; for this reason, review-collecting providers prefer to synthetically evaluate user satisfaction by considering a score on a numerical scale entered by users. To overcome this criticality, we propose an emotion detection method based on a light fuzzy-based document classification model to capture the relevance of pleasant and unpleasant emotions expressed by users in their reviews of service facilities. This method is implemented in a geo-computational framework and tested to evaluate the satisfaction of customers of theater venues located in the municipality of Naples (Italy). A fuzzy-based approach is used to classify user satisfaction according to the relevance of the emotional categories of pleasant and unpleasant. We show that our emotion detection method refines service feature pleasure assessments expressed on scales by users in their reviews

Less Automation More Information: A Learning Tool for a Post-occupancy Operation and Evaluation

Climate change and the pandemic generated an urgent need to have an effi-cient urban habitat that includes technological innovations to deal with the ecological and digital transitions. Italy counts about 14 million buildings, 12 of which are houses, responsible for more than 40% of final energy consumption, most of which is ascrib-able to users’ behavior and lifestyle. The increase in buildings’ energy performance is strongly related to a smart management of the demand and self-consumption, as well as a more effective and active involvement of the occupants: it is, therefore, pivotal to come up with user-friendly tools to measure and monitor the performance of the buildings and users’ habits. Tools to encourage the choices toward the environment’s comfort, rather than automation technologies, allowing the occupants and informa-tion systems to move in the direction of ecological transition. The aim is to create an aware “energy citizenship” for people living in efficient buildings. The proposal is a system that uses IoT technology and provides a global evaluation of the state of the house, from which can be extracted suggestions for better and virtuous behavior. The overall ecological footprint is measured based on five “cycles”: energy; environment; water; waste production; food. Collected data create an urban database that, along with big data, constitutes a set of boundary conditions that are crossed with single units’ data. The measures related to single units can be applied to a wider network in order to create a smart city, involving dwellers in a serious game on their homes’ performance. The proposal is part of the research on post-evaluation occupancy, in the belief that even the best model-houses perform worse in use, rather than the predictions expected on paper

italian High‑Speed Railway Stations and the Attractivity Index: the Downscaling Potential to Implement Coworking as Service in Station

This article introduces a methodology to evidence the current attractiveness level of Italian high-speed railway stations in a GIS environment, involving station services and fow parameters. The model has been elevant to detect stations with lower attractive capacity, and afterward, to implement the station attractivity, the work proposed employing a coworking spaces strategy as a service in station. Coworking spaces produce enefts both for the traveler and the transport company. These places became part of the services ofered within railway stations since they are fow providers able to change appearance and idea of experience at station. In France, a coworking strategy has been created from the collaboration of Regus, leader company in coworking spaces supply, and the French railway group (SNCF). The Italian railway company (Ferrovie dello Stato) does not consider the attractiveness potential of coworking in the management of station resources; coworking spaces in Italy are placed outside stations. Accordingly, Torino Porta Susa station has been identifed as one of the stations with low attractivity capacity from the methodology implemented, and it has been chosen as the case study to implement the coworking strategy. The choice of Torino Porta Susa is accurate also for showing the value of associating coworking as urban policies support. The coworking strategy can implement attractiveness levels and, in a long-term future perspective, encourage sustainable mobility target

NHERF1 acts as a molecular switch to program metastatic behavior and organotropism via its PDZ domains.

Metastatic cells are highly plastic for differential expression of tumor phenotype hallmarks and metastatic organotropism. The signaling proteins orchestrating the shift of one cell phenotype and organ pattern to another are little known. Na(+)/H(+) exchanger regulatory factor (NHERF1) is a molecular pathway organizer, PDZ-domain protein that recruits membrane, cytoplasmic, and cytoskeletal signaling proteins into functional complexes. To gain insight into the role of NHERF1 in metastatic progression, we stably transfected a metastatic breast cell line, MDA-MB-231, with an empty vector, with wild-type NHERF1, or with NHERF1 mutated in either the PDZ1- or PDZ2-binding domains to block their binding activities. We observed that NHERF1 differentially regulates the expression of two phenotypic programs through its PDZ domains, and these programs form the mechanistic basis for metastatic organotropism. The PDZ2 domain promotes visceral metastases via increased invadopodia-dependent invasion and anchorage-independent growth, as well as by inhibition of apoptosis, whereas the PDZ1 domain promotes bone metastases by stimulating podosome nucleation, motility, neoangiogenesis, vasculogenic mimicry, and osteoclastogenesis in the absence of increased growth or invasion. Collectively, these findings identify NHERF1 as an important signaling nexus for coordinating cell structure with metastatic behavior and identifies the "mesenchymal-to-vasculogenic" phenotypic transition as an essential step in metastatic progression