Traditional Neighborhood Research Articles

Attribute reduction algorithm of neighborhood rough set based on supervised granulation and its application

In neighborhood rough set theory, attribute reduction based on measure of information has important application significance. The influence of different decision classes was not considered for calculation of traditional conditional neighborhood entropy, and the improvement of algorithm based on conditional neighborhood entropy mainly includes of introducing multi granularity and different levels, while the mutual influence between samples with different labels is less considered. To solve this problem, this paper uses the supervised strategy to improve the conditional neighborhood entropy of three-layer granulation. By using two different neighborhood radii to adjust the mutual influence degree of different label samples, and by considering the mutual influence between conditional attributes through the feature complementary relationship, a neighborhood rough set attribute reduction algorithm based on supervised granulation is proposed. Experiment results on UCI data sets show that the proposed algorithm is superior to the traditional conditional neighborhood entropy algorithm in both aspects of reduction rate and reduction accuracy. Finally, the proposed algorithm is applied to the evaluation of fatigue life influencing factors of titanium alloy welded joints. The results of coupling relationship analysis show that the effect of joint type should be most seriously considered in the calculation of stress concentration factor. The results of influencing factors analysis show that the stress range has the highest weight among all the fatigue life influencing factors of titanium alloy welded joint.

Face Recognition Attendance System Method Based on Fusion of LBP and HOG

As one of the hot topics in the field of computer vision research, face recognition technology has received significant attention due to its potentiality for a wide range of applications in government as well as commercial purposes. In practical applications, although several existing face recognition methods have achieved good performances in specific scenes, they easily suffer from a sharp decline in recognition rate if affected by different conditions of light, expression, posture and occlusion. Among many factors, influences of complex illuminations on face recognition are particularly significant. To further improve the performance of the existing local binary pattern (LBP) operator, neighbourhood weighted average LBP (NWALBP) is first proposed for fully considering the strong correlations between pixel pairs in the neighbourhood, which extends the traditional LBP uni-layer neighbourhood template window to the bi-layer neighbourhood template window and calculates the weighted average of bi-layer neighbourhood pixels in each direction. Then, inspired by centre symmetric LBP (CS-LBP), centre symmetric NWALBP (CS-NWALBP) is further proposed, which can effectively reduce computation complexity by only comparing the weighted average values of the neighbourhood pixels that are symmetric about the centre pixel. Finally, by combining the merit of histogram of oriented gradient (HOG), a feature fusion algorithm named CS-NWALBP+HOG is suggested. Several experiments have eventually demonstrated that our proposed algorithms have more robust performance under complex illumination conditions if compared with many other latest algorithms.

Consuming ‘authenticity’? Reinterpreting the ‘new middle class’ in China through the lens of retailing changes

If gentrification is occurring globally, we must understand the uneven intervention of globalisation in the production of a (global) gentrifier class. This paper adopts a comparative perspective to investigate the ‘new middle class’ within China’s urban context. Through the critical examination of subtle retailing changes, it discusses how recent place-making strategies have fabricated the aura of ‘authenticity’ built upon the history of traditional residential neighbourhoods, attracting gentrifiers, whose consumption practices have transformed the retail space of a gentrified historic neighbourhood. Using Nanjing as a case study by employing qualitative research methods, this study shows that the Chinese new middle classes have yearned for modern and elitist lifestyles, with a preference for consuming Western-style goods to manifest their distinctive tastes and social status. This paper’s research findings propose the concept of Xiaozi consumption, a specific term that challenges Western-developed concepts of ‘consuming authenticity’ by highlighting the planetary indigeneity of gentrification in the Global South.

Fault monitoring of batch process based on multi-stage optimization regularized neighborhood preserving embedding algorithm

Batch process is an important type of industrial production process, and the process mechanism is complex. It is difficult to accurately describe the dynamic changes of the production process of multi-stage time-varying batch process. In addition, the data of batch process contain not only global information but also local information. The traditional neighborhood preserving embedded algorithm is used to maintain the local geometric structure of data while ignoring the global information, and the extracted latent variables cannot fully characterize batch process. Therefore, we propose a multi-stage optimization regularized neighborhood preserving embedding (ORNPE) algorithm. First, the multiple process stages are separated by affinity propagation (AP) algorithm. Second, based on maintaining local information of neighborhood preserving embedding algorithm, slow feature analysis algorithm is used to extract dynamic time-varying global information. Then, cross-entropy is used to optimize the global information, and the extraction ability of the global information is improved. Finally, a monitoring index based on support vector data description is constructed to eliminate adverse effects of non-Gaussian data for monitoring performance. The effectiveness and advantages of the proposed algorithm based on monitoring strategy are illustrated by the penicillin fermentation process and a semiconductor industry process.

FNC: A fast neighborhood calculation framework

Efficiency has always been a key issue in neighborhood calculations. This study analyzes the low efficiency of traditional neighborhood calculation and concludes that the root cause lies in the large number of repetitive and unnecessary calculations because of the large neighborhood search range. To solve the problem, this study proposes a fast neighborhood calculation framework (FNC), including a neighborhood acceleration method with respect to a single attribute and a neighborhood acceleration method with respect to joint attributes. After avoiding many repetitive and unnecessary calculations, the efficiency of the neighborhood calculation can be significantly improved, and its time complexity is reduced from O(n2) to O(nlogn). This study also proves that the proposed framework is valid for different distance functions. Also, the proposed framework is applied to the popular research on neighborhood rough set attribute reduction. L∞-norm and L2-norm are used to verify the proposed framework is valid for different distance functions in the experiments. Multiple detailed experiments have been carried out on seventeen datasets. The experimental results demonstrate that, with the reduction results unchanged, the efficiency of the accelerated algorithms by FNC is greatly improved compared to the original algorithms. The effectiveness and efficiency of the proposed framework have been well verified. All codes have been released in the open source library at http://www.cquptshuyinxia.com/FNC.html.

An Adaptive shrinkage function for image denoising based on the neighborhood characteristics

The shrinkage function has an important effect on the image denoising results. An adaptive shrinkage function is developed in this paper to shrink the small coefficients properly for image denoising based on neighborhood characteristics. The shrinkage function is determined by the number of large coefficients near the current signal coefficients. In this way, different shrinkage functions can be adaptively used to deal with different coefficients in the process of image denoising, instead of using fixed shrinkage functions. Experimental results show that the SNR of the image processed by the adaptive shrink function algorithm is better than that processed by the soft threshold, hard threshold, and neighborhood shrink algorithm. Moreover, compared with the traditional soft threshold, hard threshold and neighborhood shrink algorithm, the PSNR of the algorithm using adaptive shrink function increases by 3.68dB, 2.28dB and 0.61dB, respectively. In addition, the proposed new algorithms, soft threshold and hard threshold, are combined with empirical Wiener filtering and shift invariant (TI) scheme to compare their image noise reduction effects. The results show that the PSNR can be improved significantly by using the adaptive shrink function algorithm combined with empirical Wiener filtering and shift invariant (TI) scheme.

Moving Together

In the wake of Hurricane Katrina and the subsequent floods in New Orleans, traditional community networks and support systems were in shambles. As neo-liberal forces moved in to privatize vast swaths of society, a clash over gentrification within the city quickly set in. Newcomers to the city pushed former residents – especially Black citizens – out of their traditional neighbourhoods and simultaneously instigated cultural battles locals viewed as anathema to their understanding of home. Amid these disputes, Junebug Theatre company, the oldest Black theatre company in the city, launched a series of solidarity building artistic engagement programmes entitled Homecoming Project to educate the public on local histories. Using Black feminist theories of solidarity, I theorize this project as embodied ‘rememory’ work, utilizing Toni Morrison’s conception of rememory ‘as in recollecting and remembering as in reassembling.’ In working with community members to collect memories and then instilling audiences with these experiences through a neighbourhood-based second-line (a traditional New Orleans roaming dance and music performance that has roots in the city’s jazz funeral tradition), Homecoming Project works as an embodied memory machine. Across the Homecoming Project performances, I articulate how the project built a ‘spirit of solidarity’: a frame I develop to articulate the process of ritual-based group solidarity that acknowledges inter-group tensions while uniting allies through shared experiences of place.

Hafıza Mekânı Olarak Mahalle: Rafadan Tayfa Örneği

The issue of collective memory refers to the practices of societies to forget and remember together. Our memory has a temporal as well as spatial implication. Because space is an indispensable element in building social memory and acts as the main actor in our experience and meaning of time. In this context, the importance of memory spaces increases in societies whose history has gone through war or genocide and whose memory has been eroded by speed and technology. On the other hand, social memory exists with certain means and tends to be erased by these means. Mass media is one of the most important tools in building social memory. As a matter of fact, mass media have the potential to be determinative in what they want to be reminded, as they can cause a social amnesia by choosing what they want to be forgotten. Television is one of the oldest and most widely used mass media. Cartoons, on the other hand, have become an important element of my mass communication with the inclusion of channels that only broadcast cartoons in the broadcasting life. On the other hand, cartoons serve as an agent in the transfer of social memory to new generations. Rafadan Tayfa, which is broadcast on TRT Children's channel, is a cartoon series that is watched by children and is popular with families because it is suitable for traditional codes. The cartoon deals with the traditional neighborhood in the 1980s through a network of spaces and relations. In fact, when the whole series is examined as a whole, the effort to transfer a memory issue that started as "in our childhood" to digital media draws attention. In this study, it is aimed to deal with the neighborhood as a memory place by analyzing the content of the cartoon named Rafadan Tayfa. Keywords: Collective memory, Memory Spaces, Neighborhood, Cartoon, Rafadan Tayfa.

Promoting conservation or change? The UNESCO label of world heritage (re)shaping urban morphology in the Old Town of Lijiang, China

The UNESCO label of World Heritage can attract a high number of tourists to heritage properties for their Outstanding Universal Values (OUV). Although international studies have demonstrated the World Heritage system can contribute to stimulating cultural tourism and boosting the local economy, how this heritage-led development process promotes urban conservation and morphological changes in cities is yet to be explored adequately. This paper aims to explore the urban morphology of a historic Chinese city after its inscription on the UNESCO World Heritage List, taking the Old Town of Lijiang as case. The methods of spatial plan analysis and discourse analysis are used to analyse the data. The research findings have demonstrated that, theoretically, the Conzenian approach of urban morphology can be an effective framework for World Heritage OUV-monitoring. Methodologically, the analysis of spatial plans and multi-stakeholder interviews can reveal local urban morphology from macro to micro levels. Case-specifically in Lijiang, urban physical characteristics and building structures have been well maintained while traditional social fabric and neighbourhood networks have almost vanished. This research has incorporated the urban morphology approach into (world) heritage management in China, as well as worldwide, in order to maintain the balance between urban conservation and economic growth.

Assessment of neighborhood sustainability in terms of urban mobility: A case study in Dhaka City, Bangladesh

Abstract For achieving sustainable cities, sustainable mobility is one of the key elements. Policymakers around the world are taking different strategies to ensure sustainable urban mobility at the local level. However, sustainable urban mobility assessment at neighborhoods of a developing country received a significant research gap. This study attempts to close this research gap by deriving and comparing neighborhood sustainability based on three indicators: modal share, travel time, and travel cost, in Dhaka city, Bangladesh. Using a two-step cluster model, neighborhoods were grouped into three clusters. Study results classified 41 (44.6%) neighborhoods as sustainable, 30 (32.6%) as potentially sustainable, and 21 (22.8%) as unsustainable neighborhoods due to less positive outcomes of sustainable mobility policies. Later, median income and jobs-housing ratio value for different neighborhood types validated the classification result. Findings from this study reveal insights for transport planners, development agencies, policymakers to identify areas where mobility of the residents needs to be improved on a priority basis; advocate further research on comprehensive sustainability assessment at the neighborhood level. Highlights for public administration, management and planning: • There is a significant difference in modal share, travel time, and travel cost in neighborhoods. • A traditional neighborhood of the city is comparatively more sustainable than newly developed ones. • Neighborhoods with similar sustainability status tend to be clustered on the city scale. • Median income and jobs-housing ratio can effectively capture the difference in sustainability level in terms of urban mobility. • Sustainable urban mobility assessment can contribute city planning and development process.

Comparing cooling efficiency of shading strategies for pedestrian thermal comfort in street canyons of traditional shophouse neighbourhoods in Guangzhou, China

In the context of climate change, the outdoor thermal environment is essential for urban health, particularly in hot and humid climate zones. In most cities in southern China, traditional shophouse neighbourhoods are regarded as a reference for climate-responsive urban morphology because multiple shading strategies are integrated, including deep canyons, semi-open arcades, and vegetation. In total, four shading strategies, namely, the height-to-width ratio of canyons and arcades, tree coverage area, and orientation, are employed in this study to compare their cooling efficiency in street canyons during summer daytime. The ENVI-met is employed for the microclimatic simulations and validated by site measurement data. The impact of varying sky view factor on the physiologically equivalent temperature was quantified to assess the cooling efficiency of each shading strategy. Our results demonstrate that the cooling efficiency of orientations varies significantly with sky view factor and is negatively associated with pedestrian thermal comfort in alleys, but positive in street canyons with arcades and trees. Varying the height-to-width ratio of canyons in arcade streets presents the best cooling efficiency, except in the east-west orientation. Shading by arcades shows a slightly higher cooling efficiency than tree coverage.

The Soviet city as a landscape in the making: planning, building and appropriating Samarkand, c.1960s–80s

ABSTRACT This paper traces the changes and continuities in the cityscape of Soviet Samarkand following the launch of the mass housing campaign under Nikita Khrushchev. It examines the planning, building, appropriation, and renovation of public and private housing on the level of practices rather than policies and discourses. The paper relates these practices to the specific temporalities of Samarkand’s landscape, such as the life cycles of inhabitants, the change of seasons, or the timelines of material decay, among others. It shows that self-help building often proved to be more effective than state projects in addressing these temporalities. Drawing on site-specific cultural, material, and technical repertoires, self-help building was more than a pragmatic reaction to the housing shortage. It sustained the traditional Central Asian neighbourhood that Soviet planners hoped to banish from the urban landscape and was key to the expansion and diversification, rather than homogenization, of the ‘Soviet’ cityscape.

The sustainable semantic foundations of the traditional neighborhoods in the desert cities

The sustainable semantic foundations of the traditional neighborhoods in the desert cities

Examining neighborhood effects on residents’ daily activities in central Shanghai, China: Integrating “big data” and “thick data”

This research combines “big data” and “thick data” approaches to examine the correlation and causation between residential neighborhood features and people’s daily commuting and traveling patterns by integrating two datasets: household survey data and mobile phone data. We focus on “lilong” neighborhoods—a primary form of traditional residential neighborhood in central Shanghai. The characteristics of lilong neighborhoods are assessed using “thick data” from surveys in 105 lilongs, while residents’ daily activities are mapped out using “big data” from two weeks of mobile phone usage. We match these two datasets at neighborhood level based on their geospatial references. Four multinomial logistic regression models are developed to examine neighborhood effects on lilong residents’ daily activities. Our research confirms the major mechanisms of neighborhood effects and unravels their relative importance in shaping the patterns of residents’ daily activities. Conceptually, this study sheds new light on the understanding of how people’s life quality and wellbeing are affected by neighborhood characteristics through highlighting the importance of social interactions and the access to/quality of public facilities. Methodologically, incorporating household survey data (thick data) and mobile phone data (big data) is proven to be a novel and effective approach for examining neighborhood effects at a relatively large scale.

Edge boundary variable neighborhood strategy adaptive search for a vegetable crop land allocation problem

ABSTRACT This paper focuses on optimizing cropland allocation for planting vegetables for farmer cooperatives. In this research, planning about land allocation for crops including what to grow and what is in demand during specific periods is performed while considering important factors such as production yield per area, crop planting and harvesting time, price fluctuations of vegetables and plant incompatibility, so that farmers can plan their crops accordingly, and achieve the optimal prices and annual income. To solve the problem, the Edge Boundary Variable Neighborhood Strategy Adaptive Search (EB-VaNSAS), which is the first extension of Variable Neighborhood Strategy Adaptive Search (VaNSAS), was applied to significantly improve the solution quality of the traditional Variable Neighborhood Strategy. Two local searches, called Track Transition Method (TTM) and Multiplier Factor (MF) were developed and used for the first time in this paper. The numerical results show that the EB-VaNSAS outperforms all other proposed methods since EB-VaNSAS could find new optimal solutions more often during the simulation, while the local search-based heuristics tend to be trapped in some local optima, and the DE lacks search intensification.

Tradition-led regeneration of contemporary neighbourhoods’ spatial structures: A case study of Tehran City, Iran

Over the past decades, modernisation has been viewed by some as one of the greatest dangers to urban life, having altered neighbourhoods dramatically. The most significant problem is the destruction of traditional neighbourhoods. The authors propose that a viable solution to this problem is to regenerate the spatial structure of contemporary neighbourhoods using traditional styles and elements. The transition from traditional to modern society has created numerous styles and challenges in the Iranian urban landscape system; in particular, the city of Tehran is experiencing considerable changes in terms of visual appeal and connection to the environment. In this paper, the principles and models for traditional neighbourhoods in the city of Tehran were studied and grouped into three categories: form, function and meaning, as a guide to regenerate the spatial structure of contemporary neighbourhoods. Three neighbourhoods from different eras were selected: Oudlajan, Shahrara and Shahid Bagheri, from the Qajar period (1789–1925), the Pahlavi era (1925–79) and the modern era, respectively. Spatial models were extracted by analysing the traditional urban design of the city of Tehran in three time periods alongside patterns and principles used in the regeneration process. Following this, criteria and principles were proposed for tradition-led regeneration of the spatial structures of contemporary neighbourhoods by form (physical form system/urban landscape), function (land use system and activity/movement and access system) and meaning/perception (frameworks for public spaces).

Applying the principles governing the traditional neighborhood development (TND) approach in the Islamic Iranian city Study sample: Fahadan neighborhood of Yazd city

Applying the principles governing the traditional neighborhood development (TND) approach in the Islamic Iranian city Study sample: Fahadan neighborhood of Yazd city

COVID-19 pandemic ramifications on residential Smart homes energy use load profiles

The COVID-19 pandemic has significantly affected people’s behavioral patterns and schedules because of stay-at-home orders and a reduction of social interactions. Therefore, the shape of electrical loads associated with residential buildings has also changed. In this paper, we quantify the changes and perform a detailed analysis on how the load shapes have changed, and we make potential recommendations for utilities to handle peak load and demand response. Our analysis incorporates data from before and after the onset of the COVID-19 pandemic, from an Alabama Power Smart Neighborhood with energy-efficient/smart devices, using around 40 advanced metering infrastructure data points. This paper highlights the energy usage pattern changes between weekdays and weekends pre– and post–COVID-19 pandemic times. The weekend usage patterns look similar pre– and post–COVID-19 pandemic, but weekday patterns show significant changes. We also compare energy use of the Smart Neighborhood with a traditional neighborhood to better understand how energy-efficient/smart devices can provide energy savings, especially because of increased work-from-home situations. HVAC and water heating remain the largest consumers of electricity in residential homes, and our findings indicate an even further increase in energy use by these systems.

New neighborhoods and an iterated local search algorithm for the generalized traveling salesman problem

For a given graph with a vertex set that is partitioned into clusters, the generalized traveling salesman problem (GTSP) is the problem of finding a cost-minimal cycle that contains exactly one vertex of every cluster. We introduce three new GTSP neighborhoods that allow the simultaneous permutation of the sequence of the clusters and the selection of vertices from each cluster. The three neighborhoods and some known neighborhoods from the literature are combined into an effective iterated local search (ILS) for the GTSP. The ILS performs a straightforward random neighborhood selection within the local search and applies an ordinary record-to-record ILS acceptance criterion. The computational experiments on four symmetric standard GTSP libraries show that, with some purposeful refinements, the ILS can compete with state-of-the-art GTSP algorithms. • Effective iterated local search for generalized traveling salesman problem. • Local search uses several neighborhoods in variable neighborhood descent (VND). • Three new neighborhoods combined with traditional neighborhoods. • Random VND is compared with VND with neighborhood prioritization.

Planning of Urban Quarters, Districts and Neighbourhoods in Islam’s Holiest City: A Comparative Analytical Study

Global experiences of planning urban areas are characterised by adopting hierarchical structures from large to small structures, i.e. residential quarter (large residential area), residential district and then residential neighbourhood. Each structure is characterised according to the area, the number of people and the services required for targeting a sustainable urban environment. This concept is a milestone in urban planning in Saudi Arabia. The research attempted to discuss the general trend of planning housing projects in Saudi Arabia and the extent of applying the hierarchal concept. Three models were chosen randomly in Makkah, showing such planning hierarchy. These are Al Shawqiyyah, Al Sharaie and Al Rabwah. These projects were planned four decades ago and became a reality. Through comparative analytical methods, findings revealed ambiguity of the hierarchal planning concept in these projects. Further, the traditional neighbourhood concept was prevalent in most neighbourhoods characterised by low-density development in planning but medium and high densities in reality. The problem is getting worse as cities grow horizontally and vertically. Consistent scientific analysis based on practice and continuous meta-analysis was used. The paper calls for the need to change the current premises of housing plans and reorganise the accumulated problems according to global experiences and local standards.