Neighborhood System Research Articles

A Novel Fuzzy Structure: Infra-Fuzzy Topological Spaces

Obtaining a weaker condition that preserves some inspired topological properties is always desirable. As a result, we introduce the concept of infra-fuzzy topology, which is a subset family that degrades the concept of fuzzy topology by omitting the condition of closedness under arbitrary unions. Fundamental properties of infra-fuzzy topological spaces are investigated, including infra-fuzzy open and infra-fuzzy closed sets, infra-fuzzy interior and infra-fuzzy closure operators, and the infra-fuzzy boundary of a fuzzy set. It is not possible to expect the latter concepts to have properties identical to those in ordinary fuzzy topological spaces. More precisely, the infra-fuzzy interior of a set need not be infra-fuzzy open, and the infra-fuzzy closure and boundary of a set may not be infra-fuzzy closed. Then, employing infra-fuzzy neighborhood systems, infra-fuzzy Q-neighborhood systems, the basis of infra-fuzzy topology, and infra-fuzzy relative topology, we propose several approaches for generating infra-fuzzy topologies. Finally, we define the notions of continuity, openness, closedness, and homeomorphism of mappings in the context of infra fuzziness and investigate some of their properties and characterizations. We show that the usual characterization of earlier notions in the infra-fuzzy structure is incorrect. We demonstrate that the family of all infra-fuzzy homeomorphisms on an infra-fuzzy topological space forms a group under mappings composition. We finish this work by proving that each infra-fuzzy homeomorphism between two infra-fuzzy topological spaces produces an isomorphism on groups of infra-fuzzy homeomorphisms of the corresponding spaces.

TOPOLOGICAL MODELING OF DIGITAL INFORMATION SPACE

The article discusses modern approaches to modeling socio-economic systems and methods of modeling information flows that determine systems functioning in the information environment. Principles of modeling socio-economic systems are proposed based on considering the system as a fragment of the information network formed by a set of open interacting socio-economic systems. The properties of the socio-economic system are considered from the point of view of its inclusion in the network. The considered properties are associated not with the system name in the set, but with the functions that the system is endowed with in relation to other systems as elements of the network, which makes it possible to define such a network as a space. The concepts of a system neighborhood, which defines its near environment, and a contour as a chain of information flows, which determine the system inclusion in the information space, have been introduced. A model of digital information space is built as a system of neighborhoods that determines the topology in space. It is shown that the representation of the network as a topological space makes it possible to find for each socio-economic system such contours that determine the mission of the system in society. In this context, the task of management in the socio-economic system is formulated as maintaining its inclusion in these contours, which determines the place and importance of the system in meeting the needs of society, anticipating the emergence of new needs and inclusion in new contours to meet these needs.

A rough set model based on (L, M)-fuzzy generalized neighborhood systems: a constructive approach

Considering L and M being different commutative quantales, this paper mainly proposes a many-level version of L-fuzzy generalized neighborhood systems and then a pair of many level upper and lower rough approximation operators based on it are defined and discussed. It is proved that these approximation operators include L-fuzzy generalized neighborhood-based approximation operators and M-level L-fuzzy relation-based approximation operators as their special circumstances. Moreover, we define the measure of many level rough approximations that in a certain sense characterizes the quality of the obtained approximation. Furthermore, when the M-level L-fuzzy generalized neighborhood system is non-increasing, serial, reflexive, transitive, and unary, then the corresponding M-level L-rough approximation operators are discussed and characterized, respectively. Moreover, the relationship between M-level L-rough approximation operators and -quasi-fuzzy topologies is presented.

Multi-year planning for the integration combining distributed energy system and electric vehicle in neighborhood based on data-driven model

As more residents choose electric vehicles (EVs), the strain on the neighborhood’s energy supply will increase due to EVs’ dynamic charging requirements. Furthermore, the distributed energy system (DES) has demonstrated its benefit on local energy supply, considerably increasing its efficacy. This study concentrates on multi-year planning for the integration framework combining DES and EV charging supply in the neighborhood business center(NBC). Two types of EVs are considered, and their models are developed separately based on different stochastic behaviors. A novel data-driven method using real weather data to generate charging scenarios is proposed, which can provide quantitative guidance for planning. Latin hypercube sampling(LHS) is applied as the technical method for scenario generating. Machine learning(ML) clustering method with elbow criterion is used to conduct scenarios reduction. The multi-year planning optimization of the integration is accomplished based on two-stage stochastic programming. The multi-year planning project is employed in a NBC in Beijing. The planning result of integration cases with different external power limitations is assessed comprehensively. Other planning methods are introduced and compared. It shows that the integration case with moderate limitation can achieve a reduction of 67.8% and 31.6% respectively in economic cost and carbon emission. Furthermore, the EV satisfaction rate in varied scenarios is evaluated. What is more, the integration cases are furtherly assessed based on varied EV growth expectations. In general, the results have verified the effectiveness of the multi-year planning in neighborhood.

And as things have been they remain: Enteric disease and differential mortality among ethnic groups in early twentieth century Milwaukee

ObjectiveThis project aims to document enteric disease mortality differentials between German, Irish and Polish communities in Milwaukee, Wisconsin during the early twentieth century. At that time, residential segregation by ethnicity was common as was access to gainful employment. The Polish had the least access to adequately paid jobs and consequently resided in the area of the city adjacent to waterways used for waste disposal. MaterialsA total of 14,573 death certificates were examined for the years 1901 through 1905. The certificates include name, places of birth and death, age, sex and cause of death. MethodsDeaths from enteric diseases have been compiled for each ethnic group along with age and sex. Incomplete certificates were excluded from the analysis. ResultsA total of 1038 enteric disease deaths were noted. All ethnic groups were affected with the greatest impact in the Polish community. The highest risk was among infants and children in all ethnic groups. ConclusionsMortality differentials resulted from unequal access to safe water and sewage systems in neighborhoods segregated by ethnicity. SignificanceThe data demonstrate variation in the timing of the epidemiologic transition among communities separated by only a few kilometers. LimitationsWater- and food borne sources of enteric disease could not be differentiated. Suggestions for further researchThe effect of living conditions in these communities can be further studied by analyses of respiratory diseases. This can be expanded by detailed analyses of infant and child mortality.

Generalized neighborhood systems-based pessimistic rough sets and their applications in incomplete information systems

In this paper, we point out that Lin’s general neighborhood systems-based rough set model is an extension of Qian’s optimistic rough set model, and thus called optimistic general neighborhood systmes-based rough set model. Then we present a new rough set model based on general neighborhood systems, and prove that it is an extension of Qian’s pessimistic rough set model. Later, we study the basic properties of the proposed pessimistic rough sets, and define the serial, reflexive, symmetric, transitive and Euclidean conditions for general neighborhood systems, and explore the further properties of related rough sets. Furthermore, we apply the pessimistic general neighborhood systems-based rough set model in the research of incomplete information system, and build a three-way decision model based on it. A simple practical example to show the effectiveness of our model is also presented.

NEIGHBORHOOD INSTITUTE IN UZBEKISTAN

In this article, information about the place of residence-family, which is the main link of society, as well as the role of self-government institutions of citizens in the formation of mutual spiritual and moral relations between parents and children, that is, the neighborhood system. A brief idea was made about the extent of mutual cooperation on the basis of community – family – neighborhood concession, its effect today, as a result of the reforms carried out in the neighborhood system, the powers and opportunities of this social institution are increasing.

Robust power line extraction from aerial image using object-based Gaussian–Markov random field with gravity property parameters

The extraction of power line from aerial image with complex background is an extremely difficult task. In order to solve the drawbacks of low accuracy and insufficient stability of extraction algorithms, a novel object-based Gaussian–Markov random field with gravity property parameters (OGMRF-GPP) method is proposed. First of all, the OGMRF-GPP method extends the Gaussian–Markov model to a contactless and irregular neighborhood system. Secondly, the OGMRF-GPP method constructs a gravity property model by introducing multi-dimensional spatial correlations between line segments. The gravity property model can not only realize the high-precision adaptive estimation of the parameters of the linear regression equation, but also simplify the parameter estimation process. Finally, the power line segments extracted by OGMRF-GPP method can be fitted effectively. Experimental results show that the proposed method can extract power lines in a variety of scenes with higher accuracy compared with several other methods.

Periodic solutions to symmetric Newtonian systems in neighborhoods of orbits of equilibria

<abstract><p>The aim of this paper is to prove the existence of periodic solutions to symmetric Newtonian systems in any neighborhood of an isolated orbit of equilibria. Applying equivariant bifurcation techniques we obtain a generalization of the classical Lyapunov center theorem to the case of symmetric potentials with orbits of non-isolated critical points. Our tool is an equivariant version of the Conley index. To compare the indices we compute cohomological dimensions of some orbit spaces.</p></abstract>

Generalization of rough sets using maximal right neighborhood systems and ideals with medical applications

<abstract><p>Rough set theory is a mathematical technique to address the issues of uncertainty and vagueness in knowledge. An ideal is considered to be a crucial extension of this theory. It is an efficacious tool to dispose of vagueness and uncertainties by helping us to approximate the rough set in a more general manner. Minimizing the boundary region is one of the pivotal and substantial themes for studying the rough sets which consequently aim to maximize the accuracy measure. An ideal is one of the effective and successful followed methods to achieve this goal perfectly. So, the objective of this work is to present new methods for rough sets by using ideals. Some important characteristics of these methods are scrutinized and demonstrated to show that they yield accuracy measures greater and higher than the former ones in the other approaches. Finally, two medical applications are introduced to show the significance of utilizing the ideals in the proposed methods.</p></abstract>

BIFURCATIONS OF DOUBLE HETERODIMENSIONAL CYCLES WITH THREE SADDLE POINTS

In this paper, bifurcations of double heterodimensional cycles of an "∞" shape consisting of two saddles of (1,2) type and one saddle of (2,1) type are studied in three dimensional vector field. We discuss the gaps between returning points in transverse sections by establishing a local active coordinate system in the tubular neighborhood of unperturbed double heterodimensional cycles, through which the preservation of "∞"-shape double heterodimensional cycles is proved. We then get the existence of a new heteroclinic cycle consisting of two saddles of (1,2) type and one saddle of (2,1) type, which is composed of one big orbit linking <i>p</i>₁, <i>p</i>₃ and two orbits linking <i>p</i>₃, <i>p</i>₂ and <i>p</i>₂, <i>p</i>₁ respectively, and another heterodimensional cycle consisting of one saddle <i>p</i>₁ of (2,1) type and one saddle <i>p</i>₂ of (1,2) type, which is composed of one orbit starting from <i>p</i>₁ to <i>p</i>₂ and another orbit starting from <i>p</i>₂ to <i>p</i>₁. Moreover, the 1-fold and 2-fold large 1-heteroclinic cycle consisting of two saddles <i>p</i>₁ and <i>p</i>₃ of (1,2) type is also presented. As well as the coexistence of a 1-fold large 1-heteroclinic cycle and the "∞"-shape double heterodimensional cycles and the coexistence conditions are also given in the parameter space.

The Ribes-Zalesskii property of some one relator groups

The profinite topology on any abstract group $G$, is one such that the fundamental system of neighborhoods of the identity is given by all its subgroups of finite index. We say that a group $G$ has the Ribes-Zalesskii property of rank $k$, or is RZ$_{k}$ with $k$ a natural number, if any product $H_{1} H_{2} \cdots H_{k}$ of finitely generated subgroups $H_{1}, H_{2}, \cdots , H_{k}$ is closed in the profinite topology on $G$. And a group is said to have the Ribes-Zalesskii property or is RZ if it is RZ$_{k}$ for any natural number $k$. In this paper we characterize groups which are RZ$_{2}$. Consequently, we obtain condition under which a free product with amalgamation of two RZ$_{2}$ groups is RZ$_{2}$. After observing that the Baumslag-Solitar groups $BS (m, n)$ are RZ$_{2}$ and clearly RZ if $m= n$, we establish some suitable properties on the RZ$_{2}$ property for the case when $m= -n$. Finally, since any group $BS (m, n)$ can be viewed as a HNN-extension, then we point out the Ribes-Zalesskii property of rank two on some HNN-extensions.

Dim and Small Target Detection Based on Gaussian Markov Random Field Motion Direction Estimation

To improve the detection of dim and small targets in low signal-to-noise ratio (SNR < 3dB) scenarios, energy accumulation along the estimated direction by estimating the direction of the target’s motion at different moments is a proven approach, and considering that the Gaussian Markov random field can well describe the correlation of image element points in their air and time domains, Gaussian Markov random field is introduced into the paper to process the image. Firstly, by combining the proximity of image element spatial coordinates and the correlation of image element values to construct a new adaptive Gaussian weighted Markov random field filtering model, which fully incorporates the spatio-temporal information of image element coordinates and the correlation degree information of image element values for weighting to describe the image element neighborhood system. Second, to further enhance the energy of weak targets, the energy accumulation of targets is achieved by establishing a Gaussian Markov random field motion direction estimation model on the basis of obtaining filtered images. Through experiments, it is shown that the algorithm proposed in this paper can effectively accumulate the weak signal of the target between frames, and the target signal-to-noise ratio can reach more than 6dB compared with that before enhancement, effectively improving the detection ability of weak targets.

Improvement of Approximation Spaces Using Maximal Left Neighborhoods and Ideals

Rough set theory was introduced by Pawlak, in 1982, as a methodology to discover structural relationships within imprecise and uncertain data. This theory has been generalized using the idea of neighborhood systems to be more efficient to get rid of uncertainty and deal with a wide scope of practical applications. Motivated by this idea, in this work, we initiate novel generalized rough set models using the concepts of &#x201C;maximal left neighborhoods and ideals". Their basic features are studied and the relationships between them are revealed. The main merits of these models, as we prove, are first to preserve almost all major properties of approximation operators with respect to the Pawlak model. Second, they keep the monotonic property, which leads to an efficient evaluation of the uncertainty in the data, and third, these models enlarge the knowledge gotten from the information systems because they minimize the vagueness regions more than some previous models. We complete this manuscript by applying the proposed approach to analyze educational data and illustrate its role to improve the obtained classifications of objects and show the great performance of the present approach against other ones. Elucidative examples that support the obtained results are provided.

Subset neighborhood rough sets

We present a novel kind of neighborhood, named subset neighborhood and denoted as Sρ-neighborhood. It is defined under an arbitrary binary relation using the inclusion relations between Nρ-neighborhoods. We study its relationships with some kinds of neighborhood systems given in the literature. Then, we formulate the concepts of Sρ-lower and Sρ-upper approximations, and Sρ-accuracy and roughness measures based on Sρ-neighborhoods. We show in which cases the Sρ-accuracy measure is the highest among related approximations and investigate under which conditions the Sρ-accuracy and Sρ-roughness measures are monotonic. Moreover, we compare our approach with two existing ones and elucidate the advantages of our technique to obtain accuracy measures under some specific relations. To support the obtained results, we provide two medical examples.

China’s “Embedded Neoliberal” Home-Based Elderly Care? A State-Organised System of Neighbourhood Governance

Embedding the program of elderly care into community-based service system seems to imply that China is reorganising capacities of neighbourhood governance. The program, created by transformation of neighbourhood governance, represented the state government’s frustration with the institutional embodiment of neoliberalism. However, stimulating neighbourhood organisations in elderly care service through involvement of market instruments demonstrated the neoliberal approach. In this study, we provided a research framework in the context of embedded neoliberalism to explore the dilemma of neighbourhood governance in China. By interviewing 100 elderly people in five neighbourhoods in Nanjing, China, we examined the home-based elderly care (HEC) model to analyse the changes in socio-spatial relationships of neighbourhoods. We argued that the state-organised system of market instruments as a form of neighbourhood system weaken the spontaneity of elderly residents in developing social capitals. Moreover, the emerging program is struggling to operate because the devolution of conservative governance capacity from the state to the neighbourhood does not provide resources, leading to the restrained market provision. Thus, this transformation of neighbourhood governance can only be effective if there is a clear complementarity relationship between the role of state and market instruments. The attention of further studies on neighbourhood governance needs to re-examine the reciprocal relationships in the context of declining neoliberalism.

A whole system approach to increasing children\u2019s physical activity in a multi-ethnic UK city: a process evaluation protocol

BackgroundEngaging in regular physical activity requires continued complex decision-making in varied and dynamic individual, social and structural contexts. Widespread shortfalls of physical activity interventions suggests the complex underlying mechanisms of change are not yet fully understood. More insightful process evaluations are needed to design and implement more effective approaches. This paper describes the protocol for a process evaluation of the JU:MP programme, a whole systems approach to increasing physical activity in children and young people aged 5–14 years in North Bradford, UK.MethodsThis process evaluation, underpinned by realist philosophy, aims to understand the development and implementation of the JU:MP programme and the mechanisms by which JU:MP influences physical activity in children and young people. It also aims to explore behaviour change across wider policy, strategy and neighbourhood systems. A mixed method data collection approach will include semi-structured interview, observation, documentary analysis, surveys, and participatory evaluation methods including reflections and ripple effect mapping.DiscussionThis protocol offers an innovative approach on the use of process evaluation feeding into an iterative programme intended to generate evidence-based practice and deliver practice-based evidence. This paper advances knowledge regarding the development of process evaluations for evaluating systems interventions, and emphasises the importance of process evaluation.

A new definition of fuzzy k-pseudo metric and its induced fuzzifying structures

In this paper, a new definition of a fuzzy $k$-pseudo metric is introduced and its induced fuzzifying structures are constructed, such as a fuzzifying neighborhood system, a fuzzifying topology, a fuzzifying closure operator, a fuzzifying uniformity.Besides, it is shown that there is a one-to-one correspondence between fuzzy $k$-pseudo metrics and nests of crisp $k$-pseudo metrics.

Assignment flows for data labeling on graphs: convergence and stability

The assignment flow recently introduced in the J. Math. Imaging and Vision 58/2 (2017) constitutes a high-dimensional dynamical system that evolves on a statistical product manifold and performs contextual labeling (classification) of data given in a metric space. Vertices of an underlying corresponding graph index the data points and define a system of neighborhoods. These neighborhoods together with nonnegative weight parameters define the regularization of the evolution of label assignments to data points, through geometric averaging induced by the affine e-connection of information geometry. From the point of view of evolutionary game dynamics, the assignment flow may be characterized as a large system of replicator equations that are coupled by geometric averaging. This paper establishes conditions on the weight parameters that guarantee convergence of the continuous-time assignment flow to integral assignments (labelings), up to a negligible subset of situations that will not be encountered when working with real data in practice. Furthermore, we classify attractors of the flow and quantify corresponding basins of attraction. This provides convergence guarantees for the assignment flow which are extended to the discrete-time assignment flow that results from applying a Runge–Kutta–Munthe–Kaas scheme for the numerical geometric integration of the assignment flow. Several counter-examples illustrate that violating the conditions may entail unfavorable behavior of the assignment flow regarding contextual data classification.

Incremental updating three-way regions with variations of objects and attributes in incomplete neighborhood systems

The data collected from the real world are diverse and include categorical data, numerical data, incomplete data and noisy data. In addition, many real data sets may dynamically vary, and dynamic data display characteristics with multi-dimensional variations. However, for mixed incomplete data systems, most of the existing incremental methods only work well with single-dimensional dynamic data sets and are not suitable for processing specific multi-dimensional variations of objects and attributes. In this paper, we focus on researching dynamic approaches to efficiently update three-way regions based on the simultaneous variations of the object set and the attribute set in an incomplete neighborhood decision system (INDS). First, considering the complexity of data, we utilize matrix approaches to calculate three-way regions of the INDS based on a proposed neighborhood tolerance relation. Then, under the simultaneous addition of the object set and the attribute set in the INDS, we research incremental mechanisms based on the matrix to obtain three-way regions from previous knowledge. Subsequently, an incremental algorithm for updating three-way regions is proposed when the object set and the attribute set are simultaneously added to the INDS. Finally, the results of a series of experiments and comparisons based on UCI data sets show that the performance of the proposed incremental algorithm is much better than that of the traditional static algorithm, the integrated single-dimensional incremental algorithm and the single-level combined incremental algorithm.