Set Of Neighbors Research Articles

Feature selection for label distribution learning based on neighborhood fuzzy rough sets

Feature selection for label distribution learning based on neighborhood fuzzy rough sets

Environmental perceptions, self-regulation, and coping with noise mediate the associations between children’s physical environment and sleep and mental health problems

Children face various challenges in their home and extended neighborhood settings. In this study, we examine the impact of the built and social environments on sleep/mental health and the potential mediating role of environmental perceptions, self-regulation, and coping with noise. Cross-sectional data for 1251 schoolchildren (8-12 years) were sampled in the Tyrol region of Austria/Italy. Questionnaires provided information on sociodemographic and housing factors, perceived neighborhood quality, coping with noise during homework, self-regulation, sleep, and mental health problems. A built environment score was based on modeled levels of road and rail traffic noise, nitrogen dioxide, and imperviousness density. Home garden represented availability of accessible greenspace. Associations between predictors and mental health/sleep problems were examined using quantile regressions and structural equation modeling (SEM). In multivariate regressions, poor neighborhood quality, poor self-regulation, low traffic safety, and higher coping efforts were associated with more mental health and sleep problems. Good family relations acted in the opposite direction. In SEM, the built environment score was associated with lower neighborhood quality and lower traffic safety, which in turn led to higher coping efforts, and then to mental health/sleep problems. Home gardens related to less sleep problems through higher perceived neighborhood quality and lower coping efforts. Good family relations were associated with better mental health/sleep directly and via better self-regulation and lower coping efforts. Children forced to engage in coping activities when disturbed by noise during homework show poorer mental health. Good family relations, good neighborhood quality, and close-by greenspace may be factors to alleviate built environment stressors. The negative association of required coping with noise during homework suggests that children, in contrast to adults, may be limited in their coping abilities. Our findings call for further inquiries, as children and their environments may vary with respect to coping efficiency.

A deep embedded clustering technique using dip test and unique neighbourhood set

A deep embedded clustering technique using dip test and unique neighbourhood set

The Collection of Various βws – Closed Sets in Topological Spaces

This research presents an innovative class of Beta weakly semi-closed sets namely, The collection of various βws – closed sets in Topological spaces. Throughout this paper, βws-Semi closure sets, βws-Interior and βws – Neighbourhood sets were examined to get the fundamental facts in the Beta weakly semi-closed sets. In this paper, the notion of countable βws-semi- closed sets and βws-Interior in TS were explored and βws – Neighbourhood (βws-nbd) in TS were also studied to get results. Here, many characterizations were obtained along with some of their feature results.

Triangle Centrality

Triangle centrality is introduced for finding important vertices in a graph based on the concentration of triangles surrounding each vertex. It has the distinct feature of allowing a vertex to be central if it is in many triangles or none at all. Given a simple, undirected graph \(G=(V,E)\) with \(n=|V|\) vertices and \(m=|E|\) edges, let \(\triangle(v)\) and \(\triangle(G)\) denote the respective triangle counts of \(v\) and \(G\) . Let \(N(v)\) be the neighborhood set of \(v\) . Respectively, \(N_{\triangle}(v)\) and \(N_{\triangle}[v]=\{v\}\cup N_{\triangle}(v)\) denote the set of neighbors that are in triangles with \(v\) and the closed set including \(v\) . Then the triangle centrality for a vertex \(v\) is \(\begin{align*}TC(v)=\frac{\frac{1}{3}\sum_{u\in N_{\triangle}[v]}\triangle(u)+\sum_{w\in\{N(v)\setminus N_{\triangle}(v)\}}\triangle(w)}{\triangle(G)}.\end{align*}\) We show experimentally that triangle centrality is broadly applicable to many different types of networks. Our empirical results demonstrate that 30% of the time triangle centrality identified central vertices that differed with those found by five well-known centrality measures, which suggests novelty without being overly specialized. It is also asymptotically faster to compute on sparse graphs than all but the most trivial of these other measures. We introduce optimal algorithms that compute triangle centrality in \(O(m\overline{\delta})\) time and \(O(m+n)\) space, where \(\overline{\delta}\leq O(\sqrt{m})\) is the average degeneracy introduced by Burkhardt, Faber, and Harris (2020). In practical applications, \(\overline{\delta}\) is much smaller than \(\sqrt{m}\) so triangle centrality can be computed in nearly linear time. On a Concurrent Read Exclusive Write (CREW) Parallel Random Access Machine (PRAM), we give a near work-optimal parallel algorithm that takes \(O(\log n)\) time using \(O(m\sqrt{m})\) CREW PRAM processors. In MapReduce, we show it takes four rounds using \(O(m\sqrt{m})\) communication bits and is therefore optimal. We also derive a linear algebraic formulation of triangle centrality which can be computed in \(O(m\overline{\delta})\) time on sparse graphs.

Feeling Carcerality: How Carceral Seepage Shapes Racialized Emotions

Abstract This article examines how young people experience policing and reveals the emotional weight of the carceral state. Drawing on interviews and focus groups with over forty Black and non-Black Latinx young men in Los Angeles County, I argue that the racialized emotions the young men allude to do not stem from one individual encounter with the police or any single identifiable source. Instead, they are responses to the ongoing violence of what I describe as carceral seepage: witnessing the policing of loved ones and peers, the omnipresence of police, and the vulnerability of being criminalized across social contexts (schools, healthcare settings, neighborhood settings, etc.). Integrating theories on racialized emotions and the slow violence of policing, I use carceral seepage to show the breadth of the carceral state and demonstrate how it elicits a particular set of racialized emotional responses (or racialized emotions).

Evaluating the Influence of Basel Accord on Banking Sector of Pakistan

The papers aim to investigate how Basel III affected Pakistan's entire banking sector from 2013 to 2018. The requirements and obligations of Basel III are regarded as the most efficient tools for the banking sector. When analyzing the impact of Basel III on the banking industry, three primary considerations are made: financial size, spread, and provision for non-performing loans. Relapse investigations were utilized for checking speculation. We inferred that the general pummel of Basel III on banks is enormous, yet not all banks have totally taken on Basel III. The significance of this research lies in giving important experiences into the viability of global regulatory structures in rising economies' potential. By evaluating the Basel Accord's effect on Pakistan's banking sector, this study adds to a more extensive comprehension of how worldwide guidelines can be adjusted to neighborhood settings and how they can address explicit challenges faced by banks in emerging nations. This analysis not only reveals insight into the operational and vital changes made by Pakistani banks but also gives suggestions for policymakers to upgrade regulatory practices and monetary strength. Eventually, this research aims to illuminate future regulatory changes and work on the flexibility of Pakistan's banking sector in the face of worldwide monetary uncertainties. We propose highlighting semiannually the effects of Basel on the banking industry and conducting a comparison analysis of conventional and Islamic banks.

Combinatorial lower bounds for the Generalized Traveling Salesman Problem with Neighborhoods

Combinatorial lower bounds for the Generalized Traveling Salesman Problem with Neighborhoods

A novel ranking approach for identifying crucial spreaders in complex networks based on Tanimoto Correlation

A novel ranking approach for identifying crucial spreaders in complex networks based on Tanimoto Correlation

Discrepancy and sparsity

Discrepancy and sparsity

Estimating neighborhood-based mortality risk associated with air pollution: A prospective study

Effect modification of integrated neighborhood environment on associations of air pollution with mortality remained unclear. We analyzed data from UK biobank prospective study (n=421,650, median 12.5 years follow-up) to examine disparities of mortality risk associated with air pollution among varied neighborhood settings. Fine particulate matter (PM2.5), PM10 and nitrogen dioxide (NO2) were measured and assigned to each participants' address. Diverse ecological and societal settings of neighborhoods were integrated with principal component analysis and categorized into disadvantaged, intermediate and advantaged levels. We estimated mortality risk associated with air pollution across diverse neighborhoods using Cox regression. We calculated community-level proportions of mortality attributable to air pollutants. There was evidence of higher all-cause and respiratory disease mortality risk associated with PM2.5 and NO2 among those in disadvantaged neighborhoods. In disadvantaged communities, air pollutants explained larger proportions of deaths and such disparities persisted over past decades. Across 2010-2021, reducing PM2.5 and NO2 to 10μg/m3 (World Health Organization limits) would save 87,000 (52,000-120,000) and 91,000 (37,000-145,000) deaths of populations aged ≥40 years, with 150 000 deaths occurred in disadvantaged neighborhood settings. These findings suggested that disadvantaged neighborhoods can exacerbate mortality risk associated with air pollution.

An examination of urban green spaces usage behaviours and self-perceived mental health benefits: findings from two urban green neighbourhoods in Pakistan

ABSTRACT The present study examined urban green space users’ self-perceived mental health benefits of visiting green spaces in Pakistan – one of South Asia’s rapidly urbanizing countries. By using a quantitative-based cross-sectional survey, 384 participants were surveyed in green urban neighbourhood settings. It was found that most green space users believed that their visits to green spaces have at least some positive effects on the different parameters of their mental health, such as stress or anxiety levels, mood, energy levels, optimism levels, confidence levels, or concentration levels, among others. The study explored that the frequency and duration of green space usage and intensity of activity performed in the green space have an important role in determining the degree of the self-perceived mental health benefits of visiting green spaces, suggesting the importance of green interventions, including physical changes in the environment and social promotion activities to encourage green space usage among urban dwellers. Moreover, the study revealed low green space usage and activity intensity levels among certain sub-population groups compared to others, such as women, young adults, or the elderly, highlighting the need to ensure equity of access to green spaces for all sub-population groups and prioritize them in intervention strategies.

Gaussian-kernel weighted neighborhood preserving embedding algorithm and its application in fault detection

Fault detection in industrial processes is essential for enhancing production safety. Despite the application of the neighborhood preserving embedding (NPE) algorithm in fault detection as a manifold learning technique, a notable limitation exists-NPE overlooks local geometric structure, leading to suboptimal fault detection and occasional false alarms. This paper introduces the Gaussian kernel weighted NPE (KW-NPE) algorithm to address this challenge. Specifically designed for precise weight assignment in local structures, KW-NPE strategically employs the Gaussian kernel method to project the spatial neighborhood set and capture comprehensive local structural characteristics. The weight assignment, dependent on feature values, enhances the retention of intrinsic structure during dimensionality reduction. A novel objective function further augments this process.To assess performance, a comprehensive composite index is introduced in a case study, amalgamating the false alarm rate and fault detection rate. The effectiveness of the KW-NPE algorithm is demonstrated through extensive simulations and its application to the Tennessee Eastman process dataset, highlighting its superiority over conventional approaches.

Spatial Relations and Police Legitimacy in a Digitally Mediated World

Spatial Relations and Police Legitimacy in a Digitally Mediated World Cawthray and Bull in their study titled, “The Spatial Dimension of Police Legitimacy: An Exploration of Two Pacific Island States”, map the significance of spatial relationships – defined in terms of physical or geographical distance and social distance – in their analysis of police legitimacy in rural and remote contexts. They demonstrate the importance of connecting spatial relationships with police legitimacy by analysing empirical data from two Pacific island case studies. Their conclusion suggest that the relationship should be tested across a broader range of cases that include Global North, urban and virtual settings. This article takes up this challenge by focusing on the spatial relations of police legitimacy in urban settings embedded in a digitally mediated world. Our secondary analysis of ethnographic observational and interview data collected in neighbourhood policing settings in Belgium demonstrates how the proximity or distance between police officers in their interactions with both officers and citizens, whether constituted in neighbourhood settings or digital domains, can be linked to conceptualizations of police legitimacy. We argue that contextually defined elements of spatiality (physical, social or virtual) should be considered in assessments of how perceptions of police legitimacy shape interactions between police officers and citizens.

Group vertex magic labeling of some special graphs

For any additive abelian group $A$. Let $\mu$ be an element of $A$, a graph $G=(V,E)$ is said to be $A$-vertex magic graph if there exist a labeling function $f:V(G)\rightarrow A\setminus\{0\}$ such that $\omega(v)=\sum_{u\in N(v)} f(u)=\mu$ for any vertex $v$ of $G$, where $N(v)$ is the set of the open neighborhood of $v$. In this paper, we prove that the graphs such as wheel, Corona $C_{n}\odot mk$, subdivision of ladder and $t$-fold wheel for $t\neq n$ nor $n-2$ are $A$-vertex magic graphs. Also we prove that the subdivide wheel, helm and closed helm are $Z_{k}$-vertex magic graphs. However we prove that the triangular book and $t$-fold wheel for $t=n,n-2$ are group vertex magic graphs.

Distance-Based Fractional Dimension of Certain Wheel Networks

Distance-Based Fractional Dimension of Certain Wheel Networks

Walking on Real-world Terrain with an Ankle Exoskeleton in Cerebral Palsy.

Despite medical treatment focused on addressing walking disability, many millions of people with neurological conditions, like cerebral palsy (CP), struggle to maintain independent mobility. Lower limb exoskeletons and exosuits may hold potential for augmenting walking ability. However, it remains unknown whether these wearable robots are safe and beneficial for use outside of highly controlled laboratory environments, the demonstration of which is necessary for clinical translation. Here, we show that a lightweight, portable, ankle exoskeleton with an adaptable one-size-works-for-all assistance controller can improve energy efficiency and walking speed for individuals with CP spanning a wide spectrum of lower limb impairment in a multi-terrain real-world environment. Tested on an outdoor walking route with level, sloped, and stair terrain, robotic assistance resulted in a 15-18% (p = 0.013-0.026) reduction in estimated energy cost and a 7-8% (p = 0.001-0.004) increase in average walking speed across "shorter" 6-minute and "longer" 20-minute walking durations relative to unassisted walking. This study provides evidence that wearable robots may soon improve mobility in neighborhood, school, and community settings for individuals with CP.

Distributed temporal–spatial neighbourhood enhanced variational autoencoder for multiunit industrial plant‐wide process monitoring

AbstractProcess monitoring plays an essential role in ensuring the safe and efficient operation of multi‐unit plantwide industrial processes. However, complicated nonlinear dynamics of these processes pose enormous challenges to the plantwide process monitoring approaches. In this paper, a novel distributed temporal–spatial neighbourhood enhanced variational autoencoder (DTS‐VAE) monitoring scheme is proposed. The scheme selects the temporal and spatial neighbourhood sets of a current sample from a local unit. Time‐series correlation is utilized to construct temporal representative samples to obtain process dynamic characteristics. Likewise, spatial similarity is employed to construct spatial representative samples to obtain spatial patterns in the data. Then the reconstructed and current samples serve as the inputs for a variational autoencoder to extract features from the current sample and its neighbourhoods. Subsequently, a distributed monitor that considers the temporal–spatial characteristics is established for each unit. Finally, a comprehensive evaluation index is developed using Bayesian fusion strategy to improve monitoring performance. The proposed DTS‐VAE monitoring scheme was effectively verified on the Tennessee Eastman benchmark process and a wastewater treatment plant.

A method for finding a maximum value region with a minimum width in raster space

Given a grid of cells, each of which is assigned a numerical value quantifying its suitability for a certain use, one problem in geographic information science concerns the selection of a region, i.e. a connected set of cells, with a specified size that maximizes the sum of all their values. This task can be cast as a combinatorial optimization problem called the maximum value region problem, and exact and heuristic methods exist for its solution. While those solutions are guaranteed to be feasible (if not optimal), they may not be desirable for practical use if they contain too narrow segments (down to the width of a single cell). In this paper, we present a new variation of the maximum value region problem—the maximum value wide region problem—that requires a region to be at least as wide as a specified width. We offer a heuristic method for its solution which models a region as a set of neighborhoods and test its performance through computational experiments. Results demonstrate that the method generates good feasible solutions in terms of connectedness, size, width, and value, but requires more computing time than methods for maximum value regions without minimum width requirements.

MRAC-based dynamic consensus of linear systems with biased measurements over directed networks

MRAC-based dynamic consensus of linear systems with biased measurements over directed networks