Identification of relationship between housing difficulty and property values in urban areas

The objective of the present work is to use statistical data to identify territorial zones characterized by the correlation between urban access to services and quality of housing and the value of property ownership. While poverty is widely accepted to be an inherently multi-dimensional concept, it has proved very difficult to develop measures that both capture this multidimensionality and make comparisons over time and space easy. With this in mind, we attempt to apply a Total Fuzzy and Relative (TFR) approach, based on a fuzzy measure of the degree of association of an individual to the totality of the poor and an approach of semantic distance (Munda, 1995), based on the definition of a “fuzzy distance” as a discriminating reference to rank the availability to property in real estate market, as complement of urban poverty, in a specific case (the Italian City of Bari)

Identification of relationship between housing difficulty and property values in urban areas

The objective of the present work is to use statistical data to identify territorial zones characterized by the correlation between urban access to services and quality of housing and the value of property ownership. While poverty is widely accepted to be an inherently multi-dimensional concept, it has proved very difficult to develop measures that both capture this multidimensionality and make comparisons over time and space easy. With this in mind, we attempt to apply a Total Fuzzy and Relative (TFR) approach, based on a fuzzy measure of the degree of association of an individual to the totality of the poor and an approach of semantic distance (Munda, 1995), based on the definition of a “fuzzy distance” as a discriminating reference to rank the availability to property in real estate market, as complement of urban poverty, in a specific case (the Italian City of Bari)

Identification of relationship between housing difficulty and property values in urban areas

The objective of the present work is to use statistical data to identify territorial zones characterized by the correlation between urban access to services and quality of housing and the value of property ownership. While poverty is widely accepted to be an inherently multi-dimensional concept, it has proved very difficult to develop measures that both capture this multidimensionality and make comparisons over time and space easy. With this in mind, we attempt to apply a Total Fuzzy and Relative (TFR) approach, based on a fuzzy measure of the degree of association of an individual to the totality of the poor and an approach of semantic distance (Munda, 1995), based on the definition of a “fuzzy distance” as a discriminating reference to rank the availability to property in real estate market, as complement of urban poverty, in a specific case (the Italian City of Bari)

Design and Testing Novel One-Class Classifier Based on Polynomial Interpolation With Application to Networking Security

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A Neurally Inspired Robotic Control Algorithm for Gait Rehabilitation in Hemiplegic Stroke Patients

Abstract-Cerebrovascular accident or stroke is one of the major brain impairments that affects numerous people globally. After a unilateral stroke, sensory motor damages contralateral to the brain lesion occur in many patients. As a result, gait remains impaired and asymmetric. This paper describes and simulates a novel closed loop algorithm designed for the control of a lower limb exoskeleton for post-stroke rehabilitation. The algorithm has been developed to control a lower limb exoskeleton including actuators for the hip and knee joints, and feedback sensors for the measure of joint angular excursions. It has been designed to control and correct the gait cycle of the affected leg using kinematics information from the unaffected one. In particular, a probabilistic particle filter like algorithm has been used at the top-level control to modulate gait velocity and the joint angular excursions. Simulation results show that the algorithm is able to correct and control velocity of the affected side restoring phase synchronization between the legs

From the District Model to an Analysis by Specializations, Concentrations and Productive Clusters: The Localization of Economic Activities in Puglia

The application of multivariate techniques is widely used if you want to study phenomena or processes characterized by numerous variables that work simultaneously in time and space. The present contribution - with a view to using spatial statistical tools - intends to focus on the economic and production identities and vocations of Puglia, attempting to highlight inter-institutional relations and relationships. Thus, on the basis of the analysis of territorial and economic indicators, it has been proposed to hypothesize clusters as potential reference points and adequate functional tools for the planning and adoption of effective and appropriate regional policies of intervention

Identification of relationship between housing difficulty and property values in urban areas

The objective of the present work is to use statistical data to identify territorial zones characterized by the correlation between urban access to services and quality of housing and the value of property ownership. While poverty is widely accepted to be an inherently multi-dimensional concept, it has proved very difficult to develop measures that both capture this multidimensionality and make comparisons over time and space easy. With this in mind, we attempt to apply a Total Fuzzy and Relative (TFR) approach, based on a fuzzy measure of the degree of association of an individual to the totality of the poor and an approach of semantic distance (Munda, 1995), based on the definition of a “fuzzy distance” as a discriminating reference to rank the availability to property in real estate market, as complement of urban poverty, in a specific case (the Italian City of Bari).Urban Difficulty, Scan Statistics, Fuzzy logic, Property appraisal