For urban planning and environmental monitoring, it is essential to understand the diversity and complexity of cities to identify urban functional regions accurately and widely. However, the existing ...methods developed in the literature for identifying urban functional regions have mainly been focused on single remote sensing image data or social sensing data. The multi-dimensional information which was attained from various data source and could reflect the attribute or function about the urban functional regions that could be lost in some extent. To sense urban functional regions comprehensively and accurately, we developed a multi-mode framework through the integration of spatial geographic characteristics of remote sensing images and the functional distribution characteristics of social sensing data of Point-of-Interest (POI). In this proposed framework, a deep multi-scale neural network was developed first for the functional recognition of remote sensing images in urban areas, which explored the geographic feature information implicated in remote sensing. Second, the POI function distribution was analyzed in different functional areas of the city, then the potential relationship between POI data categories and urban region functions was explored based on the distance metric. A new RPF module is further deployed to fuse the two characteristics in different dimensions and improve the identification performance of urban region functions. The experimental results demonstrated that the proposed method can efficiently achieve the accuracy of 82.14% in the recognition of functional regions. It showed the great usability of the proposed framework in the identification of urban functional regions and the potential to be applied in a wide range of areas.
This paper analyses the effect of variety and intensity of knowledge on the innovation of regions. Employing data for Swedish functional regions, the paper tests the role of the variety (related and ...unrelated) and intensity of (1) internal knowledge generated within the region and also (2) external knowledge networks flowing into the region in explaining regional innovation, as measured by patent applications. The empirical analysis provides robust evidence that both the variety and intensity of internal and external knowledge matter for regions' innovation. When it comes to variety, related variety of knowledge plays a superior role.
The ventral visual stream is organized into units, or functional regions of interest (fROIs), specialized for processing high-level visual categories. Task-based fMRI scans ("localizers") are ...typically used to identify each individual's nuanced set of fROIs. The unique landscape of an individual's functional activation may rely in large part on their specialized connectivity patterns; recent studies corroborate this by showing that connectivity can predict individual differences in neural responses. We focus on the ventral visual stream and ask: how well can an individual's resting state functional connectivity localize their fROIs for face, body, scene, and object perception? And are the neural processors for any particular visual category better predicted by connectivity than others, suggesting a tighter mechanistic relationship between connectivity and function? We found, among 18 fROIs predicted from connectivity for each subject, all but one were selective for their preferred visual category. Defining an individual's fROIs based on their connectivity patterns yielded regions that were more selective than regions identified from previous studies or atlases in nearly all cases. Overall, we found that in the absence of a domain-specific localizer task, a 10-min resting state scan can be reliably used for defining these fROIs.
In the past, EU cohesion policy has led to some crucial shifts in European integration, the most important of which was its influence on the emergence and ensuing dynamic of EU multi-level governance ...(MLG). Its current reform – the so-called territorial dimension – helps create a new kind of region and thus significantly influences relations among the levels of European governance. European multi-level governance is undergoing a fundamental transformation, which is not directed by the European Commission through hard pressure, but rather through ideas and discourse. Which of these new regions will ‘harden’ and become stable actors in European governance, and which, by contrast, will gradually perish, remains an unanswered question.
The paper analyses migration flows with the purpose of defining functional regions at a micro level. It proposes an innovative approach to the processing of migration data. It includes a reflection ...on local level migration analysis in relation to local labour markets, and it is inspired by time geographical concepts and research into human spatial behaviour. Relevant identified migration flows are those that occur when a migrant only changes the place of permanent residence, and does not necessarily need to change workplace or most of the localities within a daily timespace context. The paper uses these migration data to delineate local migration areas (daily spatial systems) of the Czech Republic through the application of a standard rule-based procedure of functional regional taxonomy.
•Identifying relevant intrastate migration data at a micro regional level by analysis of spatial behaviour of individuals.•Use of the relevant portion of the migration data in order to define local migration areas.•Validation of the applicability of migration data to the definition of functional regions at a micro regional level.•Use of the territory of the Czech Republic as the example for the proposed approach.
Deep neural networks have been successfully applied to generate predictive patterns from medical and diagnostic data. This paper presents an approach for assessing persons with Alzheimer's disease ...(AD) mild cognitive impairment (MCI), compared with normal control (NC) persons, using the zoom-in neural network (ZNN) deep-learning algorithm. ZNN stacks a set of zoom-in learning units (ZLUs) in a feedforward hierarchy without backpropagation. The resting-state fMRI (rs-fMRI) dataset for AD assessments was obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI). The Automated Anatomical Labeling (AAL-90) atlas, which provides 90 neuroanatomical functional regions, was used to assess and detect the implicated regions in the course of AD. The features of the ZNN are extracted from the 140-time series rs-fMRI voxel values in a region of the brain. ZNN yields the three classification accuracies of AD versus MCI and NC, NC versus AD and MCI, and MCI versus AD and NC of 97.7%, 84.8%, and 72.7%, respectively, with the seven discriminative regions of interest (ROIs) in the AAL-90.
The main purpose of the article is the delimitation of functional regions in the Czech Republic based on the car transport flows. We argue that the traditionally used criteria for delimitation of ...functional regions (especially based on commuting to work flows) gradually losing their value. Therefore, we delimited functional regions as newly defined transport regions. Spatially expressed transport flows are unique indicators of complex spatial relations. We work with the daily intensities of car transport, which tend to create apparent nodal structures. Nodal structures are evident in particular at the micro-regional level, since transport flows reflect polarization between cities and their hinterlands. We use the concept of local minimum of transport intensities to delimit the boundaries of transport regions. As a result, we defined 235 functional transport regions (FTR) in the Czech Republic, which reflect the core-hinterland polarization. The delimited FTR represent logically arranged functional units, which we have subsequently compared with other types of functional regions. During these comparisons with various types of regions, we concluded that the greatest correlations are achieved with the regions of commuting to services.
•An unsupervised clustering algorithm based on divisive hierarchical clustering is proposed to cluster the functional regionsalong the electrode trajectory in DBS.•The optimal cluster result has been ...achieved through the feature group combination selection based on genetic algorithm.•The dorsoventral sizes of the STN and the STN sensorimotor region are 4.45 mm and 2.02 mm.•The features extracted from multiunit activity, background unit activity and local field potential are the most representative feature groups to identify the dorsal, d-v and ventral borders of the STN, respectively.•The clustering algorithm can not only provide valuable assistance for both neurosurgeons and stereotactic surgery robots in DBS surgery, but also help to study the anatomical size and neuron activity of the STN.
The functional regions clustering through microelectrode recording (MER) is a critical step in deep brain stimulation (DBS) surgery. The localization of the optimal target highly relies on the neurosurgeon's empirical assessment of the neurophysiological signal. This work presents an unsupervised clustering algorithm to get the optimal cluster result of the functional regions along the electrode trajectory.
The dataset consists of the MERs obtained from the routine bilateral DBS for PD patients. Several features have been extracted from MER and divided into groups based on the type of neurophysiological signal. We selected single feature groups rather than all features as the input samples of each division of the divisive hierarchical clustering (DHC) algorithm. And the optimal cluster result has been achieved through a feature group combination selection (FGS) method based on genetic algorithm (GA). To measure the performance of this method, we compared the accuracy and validation indexes of three methods, including DHC only, DHC with GA-based FGS and DHC with GA-based feature selection (FS) in other studies, on the universal and DBS datasets.
Results show that the DHC with GA-based FGS achieved the optimal cluster result compared with other methods. The three borders of the STN can be identified from the cluster result. The dorsoventral sizes of the STN and dorsal STN are 4.45 mm and 2.02 mm. In addition, the features extracted from the multiunit activity, background unit activity and local field potential are found to be the most representative feature groups to identify the dorsal, d-v and ventral borders of the STN, respectively.
Our clustering algorithm showed a reliable performance of the automatic identification of functional regions in DBS. The findings can provide valuable assistance for both neurosurgeons and stereotactic surgical robots in DBS surgery.
Urban-rural classifications are relevant tools for the implementation of economic and social policies that put emphasis on urbanisation patterns. This paper combines a specific geography with ...urban-rural classifications to increase their use by policymakers. Labour market areas, long used in economic geography and regional policies, are meaningful spatial units identifying human systems based on commuting patterns. This paper develops a functional urban-rural classification which captures the relationship between human communities, their activities and the environment. The proposal identifies natural space classes, expressed through land cover, as a relevant dimension in understanding socio-economic phenomena. The proposed method classifies the communities (of people and companies) and their territories. By simultaneously defining urban and rural areas, and the territories in between, the framework leads to obvious gains in terms of comparability and harmonisation. The characterisation of communities along the urban-rural gradient is performed by means of population density, via the geometrical abstract model of grid cells. Land cover information captures the natural space characteristics and resources available in territories; the comparison with national benchmark values allows the identification of the most significant local land cover features and their distribution along urbanisation patterns. Empirical spatial entropy and sensitivity analyses investigate spatial issues. Economic validation also supports the classification’s robustness. The method can be easily replicated because it uses free and open components.
In the framework of the territorial dimension of EU cohesion policy, the European Commission has been offering the establishment of functional regions. The response at the member state level has been ...very diverse, though. Whereas some states have established 'new regions', others have been reluctant to do so. The article argues that states and/or regions may veto the Europeanization process on the grounds of protecting their territoriality. More specifically, it avers that the more money is allocated in the member state and the less the cities are dominated by the regions, the higher the chance of differential empowerment of cities.
PDF
