Muhammad Taha Mukhtar, Syed Musa Ali Kazmi, Khola Naseem
et al.
Rapid urban expansion has fueled the growth of informal settlements in major cities of low- and middle-income countries, with Lahore and Karachi in Pakistan and Mumbai in India serving as prominent examples. However, large-scale mapping of these settlements is severely constrained not only by the scarcity of annotations but by inherent data quality challenges, specifically high spectral ambiguity between formal and informal structures and significant annotation noise. We address this by introducing a benchmark dataset for Lahore, constructed from scratch, along with companion datasets for Karachi and Mumbai, which were derived from verified administrative boundaries, totaling 1,869 $\text{km}^2$ of area. To evaluate the global robustness of our framework, we extend our experiments to five additional established benchmarks, encompassing eight cities across three continents, and provide comprehensive data quality assessments of all datasets. We also propose a new semi-supervised segmentation framework designed to mitigate the class imbalance and feature degradation inherent in standard semi-supervised learning pipelines. Our method integrates a Class-Aware Adaptive Thresholding mechanism that dynamically adjusts confidence thresholds to prevent minority class suppression and a Prototype Bank System that enforces semantic consistency by anchoring predictions to historically learned high-fidelity feature representations. Extensive experiments across a total of eight cities spanning three continents demonstrate that our approach outperforms state-of-the-art semi-supervised baselines. Most notably, our method demonstrates superior domain transfer capability whereby a model trained on only 10% of source labels reaches a 0.461 mIoU on unseen geographies and outperforms the zero-shot generalization of fully supervised models.
Este relato de experiência teve como objetivo abordar questões de gênero, feminismo e direitos humanos, utilizando o livro Malala, a menina que queria ir para a escola, de Adriana Carranca (2018), com alunos do 7º ano do ensino fundamental em uma escola pública. A história da ativista paquistanesa Malala Yousafzai serviu como base para leitura, fichamento, tertúlia literária, produção de cartas motivacionais e discussões sobre igualdade de gênero, acesso à educação e dos direitos humanos. A metodologia adotou uma abordagem participativa, com o uso de recursos visuais, como vídeos, para ampliar a compreensão e o engajamento dos estudantes. O referencial teórico fundamentou-se nas perspectivas de Spivak (2010) e hooks (2017, 2021), dialogando com teorias feministas e documentos internacionais. O estudo dessa obra incentivou reflexões sobre desigualdade de gênero e educação equitativa, promovendo a desconstrução de estereótipos e o fortalecimento da consciência crítica dos estudantes. A experiência também estimulou o protagonismo juvenil na defesa dos direitos humanos e na promoção da cultura da paz, reforçando o papel da educação na construção de uma sociedade mais justa e igualitária.
Ethnology. Social and cultural anthropology, Human settlements. Communities
Abstract Excess commuting, defined as the inefficiency resulting from spatial mismatches between residential and employment locations, poses significant challenges for urban planning and transportation systems. This study uses big data from individual vehicle trips collected in Tampa, Florida, to quantify excess commuting more accurately than traditional zonal approaches. Through the application of Linear Programming (LP) and Integer Linear Programming (ILP) models, this research measures minimum and actual commuting patterns across different spatial scales—census tract, block group, and individual trip levels. The findings reveal a clear scale effect associated with the Modifiable Areal Unit Problem (MAUP), as smaller spatial units consistently yield shorter minimum commuting distances and times and the ILP model at the individual trip level yields the least. By directly analyzing actual trips rather than simulated data, this approach provides a more precise and realistic assessment of excess commuting. The results underscore the values of methodological improvements and individual-level data in refining our understanding of excess commuting and supporting more efficient urban planning and policymaking.
Seyed Soroush Karimi Madahi, Kenneth Bruninx, Bert Claessens
et al.
Transmission System Operators (TSOs) rely on balancing energy provided by Balancing Service Providers (BSPs) to maintain the supply-demand balance in real time. Balance Responsible Parties (BRPs) can simultaneously deviate from their day-ahead schedules in response to imbalance prices, e.g., by controlling flexible assets such as batteries. According to the European Electricity Balancing Guideline, these imbalance prices should incentivize BRPs performing such implicit or passive balancing to aid the TSO in restoring the energy balance. In this paper, we demonstrate that BRPs are unintentionally offered the opportunity to exploit gaming strategies in European imbalance settlement mechanisms. This is enabled by a disconnect between sub-quarter-hourly dynamics that determine the imbalance prices and the financial settlement on a quarter-hourly basis. We illustrate this behavior in a case study of the imbalance settlement mechanisms in Belgium and the Netherlands. Our results reveal that, in both countries, BRPs can, in theory, exploit the imbalance mechanism by increasing the instantaneous system imbalance during minutes within the quarter-hour that determine the imbalance price while still contributing to restoring the system balance for the rest of the quarter-hour.
Francesco Martini, Daniele Lizzio Bosco, Carlo Barbanera
et al.
We describe a quantum variational algorithm for securities transactions settlement optimization, based on a novel mathematical formalization of the problem that includes the most relevant constraints considered in the pan-European securities settlement platform TARGET2-Securities. The proposed algorithm is designed for Noisy Intermediate-Scale Quantum devices, specifically targeting IBM's superconducting qubit machines. We adopt non-linear activation functions to encode inequality constraints in the objective function of the problem, and design customized noise mitigation techniques to alleviate the effect of readout errors. We consider batches of up to 40 trades obtained from real transactional data to benchmark our algorithm on quantum hardware against classical and quantum-inspired solvers.
Brighton Savayi Amuni, Stella Silas Karimi, Felistus Mwikali Patrick
Stakeholder engagement and participatory approaches influence the effectiveness of donor-funded projects. Participatory Monitoring and Evaluation (PM&E) methodologies ensure that local communities play an active role in decision-making, leading to more sustainable outcomes. Given the complex socio-political landscape of Kisumu Central Sub-County, there is a critical need for inclusive and context-responsive project monitoring strategies. Initiatives that have integrated local leaders, youth groups, and women-led organizations into their M&E processes tend to achieve stronger community buy-in, improved continuity, and more impactful outcomes. The current study explored the influence of stakeholder involvement in M&E on the performance of donor-funded projects in informal settlements in Kisumu Central Sub-County, Kenya. The study was guided by Stakeholder Engagement Theory. The study used a Convergent Parallel design with a sample size of 364 respondents computed using Yamanes' Sampling formula, drawn from 27 donor-funded projects in Obunga and Nyalenda informal Settlements. Purposive sampling was used for project managers, project M&E staff, and community members served, while community members were selected using stratified random sampling. The study findings revealed that there were regular opportunities for stakeholder interaction in the projects (x =4.05, SD 1.08), stakeholders contributed to the development of the organization/project (x= 3.79, SD=.940), although stakeholders' perspectives and opinions were not diligently incorporated into programming (x=2.06, SD=.879) as anticipated. The study, therefore, concluded that stakeholder involvement in M&E influenced the performance of donor-funded projects. The study recommended that the project managers in donor-funded projects need to enhance stakeholder involvement for project ownership and sustainability.
The population density of rural areas is generally lower than before due to rapid industrialization. Spatial optimized reconstruction of rural settlements is the key to rural sustainable development. Analyzing the distribution characteristics of rural settlements and their impact has profound implications for rural reconstruction. Several types of spatial distribution of rural settlements, such as clustered, random, and uniform discrete distribution, were found in China with significant regional differences. Rural settlements were denser in the southeastern regions compared to the northwestern regions. In regions such as plains, the spatial distribution of rural settlements was denser and the spatial distribution modes were mainly random and disperse. In regions such as cold alpine areas and desert fringes, the rural settlements density was low and mainly clustered. In the transition zone between hills and mountains, the density of rural settlements was high and the spatial distribution mode was mainly random. Rural settlements distribution was influenced by traditions and the economy, with economic development becoming increasingly influential. Additional factors that affected rural settlements distribution included average distance to main roadway, agricultural machinery, per capita grain production, per capita arable land, population density, elevation, precipitation, etc. Multiple distribution patterns should be used to reconstruct rural spaces in different geographical areas. Typical patterns included radially balanced, central land distribution mode; radially imbalanced distribution mode; multicore central land distribution mode, and corridor balanced and imbalanced distribution modes.
Cecília Laís Santana da Silva, José Eloízio da Costa
A pecuária leiteira é tradição no semiárido sergipano devido à sua relevância histórica e econômica como fonte de renda e de sobrevivência. Nesse sentido, Poço Redondo é hoje o município que mais produz leite em Sergipe, o que indica um processo de reorganização da bacia leiteira do Alto Sertão. Para entender em qual contexto surge este aumento produtivo, o artigo propõe analisar a inserção do pequeno produtor na cadeia produtiva do leite do povoado Santa Rosa do Ermírio face à subordinação e à assimetria. Portanto, como decurso do método e da análise qualitativa e quantitativa, as nuances da produção leiteira da “terra do leite” podem ser compreendidas como parte de uma macroestrutura do sistema econômico político e em sua relação com Poço Redondo e Sergipe.
The introduction of information and communication technology (ICT) has altered the way society operates things. ICT is used in various sectors, including agriculture. It can be used in the agricultural sector to distribute pricing and encourage agricultural commodity exports. The study aims to investigate the effect of ICT on cashew nut export in Benin using an autoregressive distributed lag (ARDL) approach. Data were collected over the period of 31 years (1990–2020) in Benin. The estimated results showed that mobile cellular telephone subscription is negatively and significantly correlated with cashew nut export in the short-run. However, in the long-run, it exhibits a positive and significant correlation. On the other hand, internet usage had no significant effect on cashew nut export in the short-run, but negatively influenced cashew nut export in the long-run. These results suggest that to increase its cashew nut export, the Beninese government should invest in technological infrastructure to improve internet access by reducing the cost of internet and increasing education that will allow farmers to better understand and use ICT.
Cities. Urban geography, Urbanization. City and country
Mirza Alim Mutasodirin, Rafi Dwi Rizqullah, Andie Setiyoko
et al.
In disease risk spatial analysis, many researchers especially in Indonesia are still modelling population density as the ratio of total population to administrative area extent. This model oversimplifies the problem, because it covers large uninhabited areas, while the model should focus on inhabited areas. This study uses settlement mapping against satellite imagery to focus the model and calculate settlement area extent. As far as our search goes, we did not find any specific studies comparing the use of settlement mapping with administrative area to model population density in computing its correlation to a disease case rate. This study investigates the comparison of both models using data on Tuberculosis (TB) case rate in Central and East Java Indonesia. Our study shows that using administrative area density the Spearman's $ρ$ was considered as "Fair" (0.566, p<0.01) and using settlement density was "Moderately Strong" (0.673, p<0.01). The difference is significant according to Hotelling's t test. By this result we are encouraging researchers to use settlement mapping to improve population density modelling in disease risk spatial analysis. Resources used by and resulting from this work are publicly available at https://github.com/mirzaalimm/PopulationDensityVsDisease.
Daniel Gysbers, Mark A. Levenstein, Gabriel Juarez
The effect of substrate topography on the settlement of coral larvae in wave-driven oscillatory flow is investigated using computational fluid dynamics coupled to a 2D agent-based simulation of individual larvae. Substrate topography modifies the boundary layer flow by generating vortices within roughness features that can be ejected into the bulk flow, directly influencing larval transport and settlement. In agreement with recent experimental findings, millimeter-scale ridged topographies were found to increase settlement compared to sub-mm feature heights. At this length scale, ridge spacing-to-height ratios of 10 to 20, spacings of more than 30 coral larval body lengths, resulted in the highest settlement rates. These optimal topographies produce a high averaged vertical velocity variance in the bulk flow, indicating that vertical larval movement to benthic surfaces is dominated by passive transport driven by recirculatory flow structures. Indeed, larval settlement was found to be positively correlated with mean vertical velocity variance, and settlement results with substrates comprising complex multiscale roughness were quantitatively similar to those with a simple rectangular model. Our findings reveal how substrates can be designed with surface features to promote larval settlement in natural flow conditions above shallow coral reefs independent of biological cues and substrate material composition.
Saud Alghumayjan, Jiajun Han, Ningkun Zheng
et al.
This paper presents an integrated model for bidding energy storage in day-ahead and real-time markets to maximize profits. We show that in integrated two-stage bidding, the real-time bids are independent of day-ahead settlements, while the day-ahead bids should be based on predicted real-time prices. We utilize a transformer-based model for real-time price prediction, which captures complex dynamical patterns of real-time prices, and use the result for day-ahead bidding design. For real-time bidding, we utilize a long short-term memory-dynamic programming hybrid real-time bidding model. We train and test our model with historical data from New York State, and our results showed that the integrated system achieved promising results of almost a 20\% increase in profit compared to only bidding in real-time markets, and at the same time reducing the risk in terms of the number of days with negative profits.
Isar Nejadgholi, Maryam Molamohammadi, Kimiya Missaghi
et al.
While AI has been frequently applied in the context of immigration, most of these applications focus on selection and screening, which primarily serve to empower states and authorities, raising concerns due to their understudied reliability and high impact on immigrants' lives. In contrast, this paper emphasizes the potential of AI in Canada's immigration settlement phase, a stage where access to information is crucial and service providers are overburdened. By highlighting the settlement sector as a prime candidate for reliable AI applications, we demonstrate its unique capacity to empower immigrants directly, yet it remains under-explored in AI research. We outline a vision for human-centred and responsible AI solutions that facilitate the integration of newcomers. We call on AI researchers to build upon our work and engage in multidisciplinary research and active collaboration with service providers and government organizations to develop tailored AI tools that are empowering, inclusive and safe.
Vedran Sekara, Andrea Martini, Manuel Garcia-Herranz
et al.
High-resolution human settlement maps provide detailed delineations of where people live and are vital for scientific and practical purposes, such as rapid disaster response, allocation of humanitarian resources, and international development. The increased availability of high-resolution satellite imagery, combined with powerful techniques from machine learning and artificial intelligence, has spurred the creation of a wealth of settlement datasets. However, the precise agreement and alignment between these datasets is not known. Here we quantify the overlap of high-resolution settlement map for 42 African countries developed by Google (Open Buildings), Meta (High Resolution Population Maps) and GRID3 (Geo-Referenced Infrastructure and Demographic Data for Development). Across all studied countries we find large disagreement between datasets on how much area is considered settled. We demonstrate that there are considerable geographic and socio-economic factors at play and build a machine learning model to predict for which areas datasets disagree. It it vital to understand the shortcomings of AI derived high-resolution settlement layers as international organizations, governments, and NGOs are already experimenting with incorporating these into programmatic work. As such, we anticipate our work to be a starting point for more critical and detailed analyses of AI derived datasets for humanitarian, planning, policy, and scientific purposes.
The cultural landscape in traditional settlements is an important historical and cultural resource created by human beings in the process of historical evolution, and is an important resource for the development of traditional settlement tourism. This paper selected 21 representative traditional settlements for research using online comments from tourists as data and content analytical methods including high-frequency vocabulary, semantic networks and emotional attitudes to explore the public perspective on the connotations of cultural landscape features in traditional settlements. There are four major findings, showing first that the cultural landscape of traditional settlements contains three core elements. Second, the semantic network relationships of the core elements show a significant central–edge tendency; and third, the emotional perception of cultural landscapes in traditional settlements is generally positive, and there is no significant difference emotionally between each core element. Last, the public’s perception of the cultural connotations of the landscape is seriously insufficient. Based on the research results, planning suggestions and countermeasures for the conservation and utilization of cultural landscapes in traditional settlements are proposed.
Carlos Gracia-Lázaro, Alexis R. Hernández, Felipe Maciel-Cardoso
et al.
We present an agent-based model that explores the relationship between pro-family and prosocial behaviors and their impact on settlement formation. The objective is to investigate how the technological level and various constraints influence the transition from pro-family to prosocial behavior. The model incorporates factors such as the specialization requirements of the technology, societal tolerance, and dynamic interactions within a synthetic population, where individuals have the choice to prioritize either their family or their own settlement. Agents' fitness is determined by two components: the proportion of pro-family agents within their family and the fraction of prosocial agents in their settlement, as well as its size. Our findings reveal that the transition from pro-family to prosocial behavior is driven by the technological level, and the developmental requirements of the technology shape the smoothness of this transition, ranging from abrupt to gradual. These results emphasize the significance of considering the interplay between the technological level, the nature of the technology, and cultural influences when examining settlement patterns and the dynamics of pro-family and prosocial behaviors in human societies.
Tri Wiyoko, Yogi Irdes Saputra, Aprizan Aprizan
et al.
Parents have an important role in guiding each of their children’s development, especially in choosing children’s learning literacy media during the COVID-19 pandemic. This is so that the time given to study from home can be used as well as possible. This mentoring activity was carried out in Sungai Kapas village. The method applied is service learning which consists of planning, implementation and evaluation. There were 15 participants who took part in this activity. The results of the service evaluation show that parents who realize the importance of accompanying their children in choosing literacy sources are 100%. Then the parents who are ready to accompany their children in completing their learning tasks are 85%. This shows that parental assistance for the use of learning media literacy for elementary school children in Sungai Kapas has a good effect. Parents increase their knowledge and awareness to pay attention to their children when learning. The commitment to provide assistance to children is the key to the success of the role of parents in monitoring children’s learning development during the COVID-19 pandemic by choosing learning literacy media that are appropriate for their age. The success or failure of children in understanding the material assigned by the school during learning from home is strongly influenced by parents.
Aflaj (plural of falaj) are tunnels or trenches built to deliver groundwater from its source to the point of consumption. Support vector machine (SVM) and extreme gradient boosting (XGB) machine learning models were used to predict groundwater aflaj potential in the Nizwa watershed in the Sultanate of Oman (Oman). Nizwa city is a focal point of aflaj that underlies the historical relationship between ecology, economic dynamics, agricultural systems, and human settlements. Three hyperparameter algorithms, grid search (GS), random search (RS), and Bayesian optimisation, were used to optimise the parameters of the XGB model. Sentinel-2 and light detection and ranging (LiDAR) data via geographical information systems (GIS) were employed to derive variables of land use/land cover, and hydrological, topographical, and geological factors. The groundwater aflaj potential maps were categorised into five classes: <i>deficient</i>, <i>low</i>, <i>moderate</i>, <i>high</i>, and <i>very high</i>. Based on the evaluation of accuracy in the training stage, the following models showed a <i>high</i> level of accuracy based on the area under the curve: Bayesian-XGB (0.99), GS-XGB (0.97), RS-XGB (0.96), SVM (0.96), and XGB (0.93). The validation results showed that the Bayesian hyperparameter algorithm significantly increased XGB model efficiency in modelling groundwater aflaj potential. The highest percentages of groundwater potential in the <i>very high</i> class were the XGB (10%), SVM (8%), GS-XGB (6%), RS-XGB (6%), and Bayesian-XGB (6%) models. Most of these areas were located in the central and northeast parts of the case study area. The study concluded that evaluating existing groundwater datasets, facilities, current, and future spatial datasets is critical in order to design systems capable of mapping groundwater aflaj based on geospatial and ML techniques. In turn, groundwater protection service projects and integrated water source management (IWSM) programs will be able to protect the aflaj irrigation system from threats by implementing timely preventative measures.
Lukasz Czekaj, Tomasz Biegus, Robert Kitlowski
et al.
This paper covers automated settlement of receivables in non-governmental organizations. We tackle the problem with entity matching techniques. We consider setup, where base algorithm is used for preliminary ranking of matches, then we apply several novel methods to increase matching quality of base algorithm: score post processing, cascade model and chain model. The methods presented here contribute to automated settlement of receivables, entity matching and multilabel classification in open-world scenario. We evaluate our approach on real world operational data which come from company providing settlement of receivables as a service: proposed methods boost recall from 78% (base model) to >90% at precision 99%.