Search Results (185)

This article presents a social and historical analysis of Barranco district in Lima, Peru, examining its evolution as a postmodern tourism destination. Through documentary analysis of historical records, guidebooks, press articles, and novels, we investigate the significant social milestones along history with cultural, and economic impacts on tourism development in Barranco. The research employs a methodology to identify key elements that have shaped Barranco’s trajectory from a fishing settlement to a bohemian district in a lively city and finally to its status as a “hipster” neighbourhood. Drawing on postmodern tourism theory and Hawley’s socioeconomic development theory, we argue that Barranco represents a distinctive case of how cultural capital transforms and resignifies tourism spaces through complex identity processes. Findings reveal that Barranco’s development follows three clear phases: rural settlement (until the 19th century), seaside resort (mid-19th century to 1940s–60s), and urban district with postmodern tourism appeal (1990s onward). The study concludes that while Barranco’s bohemian and artistic identity has become a distinctive tourism asset, the district faces gentrification challenges that threat its sociocultural diversity and authenticity. This research contributes to understanding how postmodern tourism influences territorial identity transformation and illuminates the social, historical, and economic forces that shape distinctive urban tourism destinations. Full article

Climate adaptation in urban environments is often constrained by rigid institutional rules and fragmented governance, which limit inclusive and context-specific planning of public spaces such as schoolyards. This study addresses this challenge by examining how collaborative planning can transform schoolyards, from asphalt-dominated, monofunctional spaces into green, climate-resilient community assets. The research employed the Institutional Analysis and Development framework within a qualitative case study design. Two public schools in the San Cristóbal de los Ángeles neighbourhood of Madrid served as case studies, with data collected through document analysis, participant observation, and interviews with municipal officials, urban planners, educators, and community members. Results indicate that the collaborative planning process reshaped rules in use, expanded the network of actors, and transformed decision-making processes. Existing rules were flexibly reinterpreted to allow new uses of space. Children, teachers, and residents became co-producers of the public space, expanding the governance network, where new deliberative practices emerged that improved coordination across people and organisations. These institutional changes occurred without formal regulatory reform, but with the reinterpretation of the game’s rules by each organisation. Thus, schoolyards can serve as laboratories for institutional innovation and participatory climate adaptation, demonstrating how urban experiments have the potential to catalyse not only physical transformations but also transformations in urban management. Full article

The remanufacturing of end-of-life products is an effective approach to alleviating resource shortages, environmental pollution, and global warming. As the initial step in the remanufacturing process, the quality and efficiency of disassembly have a decisive impact on the entire workflow. However, the complexity of product structures poses numerous challenges to practical disassembly operations. These challenges include not only conventional precedence constraints among disassembly tasks but also sequential dependencies, where interference between tasks due to their execution order can prolong operation times and complicate the formulation of disassembly plans. Additionally, the inherent uncertainties in the disassembly process further affect the practical applicability of disassembly plans. Therefore, developing reliable disassembly plans must fully consider both sequential dependencies and uncertainties. To this end, this paper employs a chance-constrained programming model to characterise uncertain information and constructs a multi-objective sequence-dependent disassembly line balancing (MO-SDDLB) problem model under uncertain environments. The model aims to minimise the hazard index, workstation time variance, and energy consumption, achieving a multi-dimensional optimisation of the disassembly process. To efficiently solve this problem, this paper designs an innovative multi-objective adaptive large neighbourhood search (MO-ALNS) algorithm. The algorithm integrates three destruction and repair operators, combined with simulated annealing, roulette wheel selection, and local search strategies, significantly enhancing solution efficiency and quality. Practical disassembly experiments on a lithium-ion battery validate the effectiveness of the proposed model and algorithm. Moreover, the proposed MO-ALNS demonstrated a superior performance compared to other state-of-the-art methods. On average, against the best competitor results, MO-ALNS improved the number of Pareto solutions (NPS) by approximately 21%, reduced the inverted generational distance (IGD) by about 21%, and increased the hypervolume (HV) by nearly 8%. Furthermore, MO-ALNS exhibited a superior stability, providing a practical and feasible solution for disassembly optimisation. Full article

Power transmission lines transfer energy between power plants and substations by means of a linear chain of towers. These towers are often situated over extensive distances, sometimes in regions that are difficult to access. Wireless sensor networks present a viable solution for monitoring these long chains of towers due to their wide coverage, ease of installation and cost-effectiveness. The proposed LoRaBUS approach implements and analyses the benefits of a linear topology using a mixture of LoRa and LoRaWAN protocols. This approach is designed to enable automatic detection of nearby nodes, optimise energy consumption and provide a prioritised transmission mode in emergency situations. On remote, hard-to-reach towers, a prototype fire protection system was implemented and tested. The results demonstrate that LoRaBUS creates a self-configurable linear topology which proves advantageous for installation processes, node maintenance and troubleshooting node failures. The discovery process collects data from a neighbourhood to construct the network and to save energy. The network’s autonomous configuration can be completed within approximately 2 min. In addition, energy consumption is effectively reduced 25% by dynamically adjusting the transmission power based on the detected channel quality and the distance to the nearest neighbour nodes. Full article

This paper addresses the need to decarbonize built environments by altering community planning and home design. By employing principles of Circular Economy at the community and dwelling levels, the paper argues that having flexible design strategies can contribute to the reduction of the carbon footprint of urban areas by minimizing the need for demolition and, as a result, material waste. Currently, depending on location and cultural and economic conditions, large-scale developments might take many years to approve and construct. Moreover, when changes are to be introduced to an initially approved masterplan, the process of obtaining municipal planning approval can be lengthy. By using a case study-based methodology for community and home design, this research argues that, given the rapidly emerging new social challenges, neighbourhoods can be designed to adapt and accommodate changes they may encounter throughout their development and in subsequent years. The proposed approval procedure that this research introduces provides a step-by-step approach to planning that can be readily adjusted based on market demand and newly developing economic and social conditions. To demonstrate his research in partnership with a private developer and the municipality, the author utilized these techniques in the design of a community in La Prairie, a town near Montreal, in Quebec, Canada. The paper also introduces the concepts of adaptability and circularity at the dwelling unit level to minimize demolition and waste. The energy efficient design incorporates demountable partitions and specialized conduits for the installation and improvement of utility lines. By investigating the macro and micro levels, the author concludes that changes to the current system, while considering the needs of key stakeholders, stand to reduce demolition and waste. Full article

The rapid development of artificial intelligence (AI) has significantly enhanced productivity, particularly in repetitive tasks. In the scientific domain, literature review stands out as a key area where AI-based tools can be effectively applied. This study presents a methodology for developing a search strategy for systematic reviews using AI tools. The Semantic Scholar database served as the foundation for the search process. The methodology was tested by searching for scientific papers related to batteries and hydrogen vehicles with the aim of enabling an evaluation for their potential applications. An extensive list of vehicles and their operational environments based on international standards and literature reviews was defined and used as the main input for the exemplary search. The AI-supported search yielded approximately 60,000 results, which were subjected to an initial relevance assessment. For the relevant papers, a neighbourhood analysis based on citation and reference networks was conducted. The final selection of papers, covering the period from 2013 to 2023, included 713 papers assessed after the initial review. An extensive discussion of the results is provided, including their categorisation based on search terms, publication years, and cluster analysis of powertrains, as well as operational environments of the vehicles involved. This case study illustrates the effectiveness of the proposed methodology and serves as a starting point for future research. The results demonstrate the potential of AI-based tools to enhance productivity when searching for scientific papers. Full article

Efficient estimation methods for simultaneous autoregressive (SAR) models with missing data in the response variable have been well explored in the literature. A common practice is introducing measurement error into SAR models to separate the noise component from the spatial process. However, prior studies have not considered incorporating measurement error into SAR models with missing data. Maximum likelihood estimation for such models, especially with large datasets, poses significant computational challenges. This paper proposes an efficient likelihood-based estimation method, the marginal maximum likelihood (ML), for estimating SAR models on large datasets with measurement errors and a high percentage of missing data in the response variable. The spatial autoregressive model (SAM) and the spatial error model (SEM), two popular SAR model types, are considered. The missing data mechanism is assumed to follow a missing-at-random (MAR) pattern. We propose a fast method for marginal ML estimation with a computational complexity of $O\left(n^{3/2}\right)$, where n is the total number of observations. This complexity applies when the spatial weight matrix is constructed based on a local neighbourhood structure. The effectiveness of the proposed methods is demonstrated through simulations and real-world data applications. Full article

This paper introduces a new method for the region segmentation of images. The approach is based on the raster-scan paradigm and builds the segments incrementally. The pixels are processed in the raster-scan order, while the construction of the segments is based on a distance metric in regard to the already segmented pixels in the neighbourhood. The segmentation procedure operates in linear time according to the total number of pixels. The proposed method, named the RSM (raster-scan segmentation method), was tested on selected images from the popular benchmark datasets MS COCO and DIV2K. The experimental results indicate that our method successfully extracts regions with similar pixel values. Furthermore, a comparison with two of the well-known segmentation methods—Watershed and DBSCAN—demonstrates that the proposed approach is superior in regard to efficiency while yielding visually similar results. Full article

Neighbourhood micro-renewal (NMIR) plays a critical role in the renewal landscape of urban China. However, an oversight in post-occupancy evaluation (POE) impedes the comprehensive understanding of NMIR’s impact and post-implementation efficacy. This research addresses this gap by leveraging the lens of place value to examine NMIR’s outcomes. Using Wuhan, China, as a case study, 10 Delphi consultations and 28 interviews were conducted among five stakeholder groups: local government, planning professionals, academics, community workers, and residents. Analytic Hierarchy Process (AHP) and Fuzzy Comprehensive Evaluation (FCE) were combined to identify and rank potential indicators. A total of 6 primary and 22 secondary indicators were identified. The indicators were derived from four key policy areas—health, society, economy, and environment—highlighting the relationship among NMIR initiatives, their contribution to place quality, and alignment with policy goals. AHP and FCE results reveal substantial enhancements in environmental quality, residential properties, and public infrastructure. Nevertheless, the analysis exposes varied satisfaction levels and divergences in the perceived relevance of indicators among the government, professionals, and the residents, particularly concerning social cohesion. These disparities underscore the layered impacts of NMIR. This research recommends integrating resident feedback with expert insights to enhance place quality in NMIR projects by balancing physical upgrades with social considerations. It also advocates for a continuous, adaptable post-occupancy evaluation system to monitor and support place value over time. This system should be flexible and context-specific, allowing NMIR initiatives to adapt to diverse urban settings globally, thus supporting long-term sustainability and thriving urban communities. Full article

The traditional A* algorithm faces the challenges of low search efficiency and large node extension range in the field of path planning. These directly restrict the overall performance of the algorithm. In this study, we aimed to improve the search efficiency and path planning quality of the A* algorithm in complex and large-scale environments through a series of optimisation measures, including the innovation of weight design, flexible adjustment of the search neighbourhood, improvement of the heuristic function, and optimisation of the node selection strategy. Specifically, this study innovatively introduces the local obstacle rate as the core index of weight design, and it dynamically adjusts the weights according to the change of the obstacle rate during the node movement process, which effectively reduces the search space and significantly improves the search speed. At the same time, according to the real-time change of the local obstacle rate, this study dynamically adjusts the range of the search neighbourhood, so that the algorithm can choose the optimal search strategy according to different environmental information. In terms of the improvement of the heuristic function, this study adopted the diagonal distance as the benchmark for cost estimation, and it innovatively introduces the angle coefficient to reflect the complexity of path turning, thus providing the algorithm with a more accurate guidance for the search direction. In addition, this study optimises the node selection method by drawing on the idea of simulated annealing, which eliminates the need to calculate and compare all possible surrogate values during the node selection process, thus significantly reducing the running time of the algorithm. The results of the simulation experiments fully verify the effectiveness and practicality of the improved algorithm. Compared with the traditional A* algorithm, the improved algorithm achieved significant optimisation in terms of the average running time, the number of expansion nodes, and the path length, with the average running time shortened by 84%, the number of expansion nodes reduced by 94%, and the path length also shortened by 2.3%. Full article

Digital technology has brought drastic changes to the design methods, values, and design tools of neighbourhood public spaces, thereby changing the behavioural patterns of people in neighbourhood public spaces. Therefore, people’s requirements for urban public space have changed and are characterised by high efficiency, high precision, humanization, and high aesthetics. Scholars at home and abroad have conducted many studies and practises on the application of digital technology to neighbourhood design, but there is a lack of systematic research practises on the use and analysis of multi-faceted data. This paper selects the Xiaomi Beijing Changping II design project, simulates and deduces the physical environment of its location, simulates the results of the natural environment by using the data of sunshine, wind, and water catchment in the physical environment, and then simulates the crowd’s action paths by combining kinetic algorithms and ant algorithms to optimise the design methods, processes, and results of the neighbourhood public space on the basis of this research. The research team designed five groups of programmes for the project based on different design methods and processes, and conducted a comparative study of the five groups of programmes through the hierarchical analysis method in conjunction with the fuzzy comprehensive evaluation method, as well as discussing them in conjunction with the actual bidding results of the project and the scoring conclusions of the industry experts. The results of the study show that the design scheme for neighbourhood public space based on physical environment simulation and crowd simulation is better able to take advantage of the analytical and predictive advantages of the technology and unite with the designer’s aesthetic interests, balancing the data objectivity and aesthetic subjectivity in the design process. The method is more likely to achieve a design solution that combines systematicity, foresight, rationality, and aesthetics, and provides an empirical case for the application of data simulation in public space, aiming to improve the rationality of public space design and solve the data-objective problems faced by the design of public space at this stage. Full article

Based on bee foraging behaviour, the Bees Algorithm (BA) is an optimisation metaheuristic algorithm which has found many applications in both the continuous and combinatorial domains. The original version of the Bees Algorithm has six user-selected parameters: the number of scout bees, the number of high-performing bees, the number of top-performing or “elite” bees, the number of forager bees following the elite bees, the number of forager bees recruited by the other high-performing bees, and the neighbourhood size. These parameters must be chosen with due care, as their values can impact the algorithm’s performance, particularly when the problem is complex. However, determining the optimum values for those parameters can be time-consuming for users who are not familiar with the algorithm. This paper presents BA₁, a Bees Algorithm with just one parameter. BA₁ eliminates the need to specify the numbers of high-performing and elite bees and other associated parameters. Instead, it uses incremental k-means clustering to divide the scout bees into groups. By reducing the required number of parameters, BA₁ simplifies the tuning process and increases efficiency. BA₁ has been evaluated on 23 benchmark functions in the continuous domain, followed by 12 problems from the TSPLIB in the combinatorial domain. The results show good performance against popular nature-inspired optimisation algorithms on the problems tested. Full article

Bilingual acquisition research has so far focused on comparisons with monolingual children in terms of linguistic features, performance on standardised tests, input, etc. In contrast, new methodologies, such as eye-tracking, can offer a more detailed understanding of the way bilinguals use both language systems. Eye fixations provide evidence of online processing. This study investigates spoken word recognition in children and adults. Word retrieval is affected by the number of words that minimally differ from the target (neighbourhood). Previous research found that only bilingual adults activated a similar-sounding competitor from the other language. As children have been found to be sensitive to neighbourhood density from quite early in previous research, similar results might be expected. This study includes 56 subjects (11 German–English bilingual and 12 English monolingual children, aged 8; 21 English monolingual and 12 German–English bilingual adults). The subjects’ online processing of competing items for high- and low-density targets was compared. The results confirm that neighbourhood density affects word recognition in adults and children. The bilingual children activated same-language competitors as well as similar-sounding competitors from the other language. Adults and children differed in terms of latencies, and the monolinguals were more accurate than the bilingual subjects. Full article

The scientific literature has revealed that there is often a discrepancy between urban planning initiatives and the actual development of cities. Urban development is a complex process strongly affected by the self-organisation of citizens and entrepreneurs, who produce services and events, create new public places, and shape urban regeneration through everyday practices. However, the actors of self-organised urban development are rarely met in participatory urban planning practices. The gap raises the research problem of how to recognise and facilitate civic engagement in urban development. The authors of this article have been investigating the ontology and methodology of urban planning and development over the past two decades, culminating in the framework of expanded urban planning. The article aims to present multiple approaches to civic engagement in urban planning and development, based on an updated longitudinal study conducted in a Helsinki neighbourhood. The authors argue that urban planning should be updated with expanded urban planning (EP), which extends the focus of civic engagement from public participation to self-organisation and everyday life practices. Full article

People responsible for shaping the future of cities often seek valuable tools to assist in their decision-making processes. Using objective, quantified, and analysed data proves highly beneficial when determining where to focus interventions at the city level. Various urban indexes have been established to measure different aspects of urban life, ranging from sustainability to liveability. These indexes encompass multiple dimensions of a city, including mobility and walkability, among others. The age-friendly cities initiative developed indicators for assessing the age-friendliness of cities. Some researchers further refined these indicators to focus on urban planning competencies. Building on this foundation, this article aims to present an Age-Friendly Neighbourhood Index (AFNI) validated by a panel of experts using the Delphi method. This index can serve as a valuable tool for urban planners when they need to prioritise interventions to enhance age-friendliness at neighbourhood scale. The article also outlines the necessary data and measurement techniques for these indicators. The AFNI has been applied to a real case study in the city of Santander (Spain). This application assesses the age-friendliness of various neighbourhoods in Santander, demonstrating the challenges in acquiring sub-local quality data and emphasising the need for data-driven urban management. Full article