Infrastructure Elements Research Articles (Page 1)

This study assessed the inclusivity of the Dar es Salaam Bus Rapid Transit (DART) system by examining how its physical conditions support passengers with disabilities. The objective was to evaluate key infrastructural elements – ramps, wheelchair-friendly stations, and accessible seating – and analyse staff preparedness and passenger experience using the Theory of Planned Behaviour and Service Quality Theory. A mixed approach and descriptive cross-sectional research design was used, employing stratified random sampling of 178 Dar es Salaam Rapid Transit (DART) staff and purposive sampling for five zonal station leaders and snowball sampling for selecting 100 passengers with disabilities. Data were collected through structured questionnaires and analysed using SPSS (Version 26). Quantitative findings were presented through descriptive statistics, while narrations presented the qualitative findings that were analysed through content analysis. The findings reveal that while some inclusive infrastructure such as ramps and reserved seating exists, functionality is compromised by poor design, maintenance gaps, signage deficiencies, and lack of enforcement. Additionally, training among frontline staff is inconsistent and inadequate, further impeding service delivery. The study concludes that Dar es Salaam Rapid Transit (DART) had to deliver transport that is equitable and inclusive for people with disabilities. The recommendations were made on the provision of regular staff training, improvements in accessibility features, and stronger enforcement of inclusive policies.

ABSTRACT This article analyses the recruitment of Filipino caregivers to Israel through the lens of migration infrastructures, based on original fieldwork conducted in 2011 and 2019. Using Xiang and Lindquist’s framework, we examine how regulatory, commercial, and social infrastructures interact to shape the migration process. We propose a typology of commercial infrastructures – first-order (recruitment agencies), second-order (training, medical, and documentation services), and third-order (logistical support such as housing and transportation) – to capture the layered and expanding structure of the migration industry. Our findings show that, over time, the recruitment process has become more complex, institutionalised, and commodified. The expansion of facilitative services illustrates the process of infrastructuralisation, in which the infrastructure itself becomes the central object of growth. Concomitantly, the rising costs and density of intermediaries reflect infrastructural involution, whereby expanded infrastructure increases burdens on migrants without improving outcomes. By disaggregating the elements of the commercial infrastructure and tracing their evolution over time, we provide a deeper understanding of how precariousness is embedded in the very systems designed to facilitate labour mobility.

IntroductionIn the process of urbanization, public space plays an increasingly important role in improving the livability and sustainability of cities. However, effectively understanding the preferences of different groups for public space and conducting reasonable planning integrated with environmental and infrastructure elements remains a challenge in urban planning. This is because traditional planning methods often fail to fully capture the detailed behavior of residents. Therefore, the purpose of this study was to explore the empirical application of machine learning technology to public space planning along the Grand Canal in Shandong Province (China), analyze the behavior patterns and preferences of residents regarding different public spaces, and thereby provide support for data - driven public space planning.MethodsBased on survey data from 1008 respondents across 4 cities, this study employed machine learning methods such as K - means clustering, association rule mining, and correlation analysis to investigate the relationships between visitor behavior and the environmental characteristics of public spaces.ResultsThe application of these methods yielded several important results. Cluster analysis identified three distinct groups: young and middle - aged local residents with a preference for accessibility, middle - aged and elderly groups enthusiastic about cultural engagement, and diverse transportation users with mixed spatial preferences. Additionally, association rule mining uncovered strong correlations between location types and perceived attributes such as cleanliness and aesthetics. Moreover, correlation analysis indicated statistically significant positive correlations between aesthetics and cleanliness, as well as between safety and cleanliness.DiscussionThis research offers valuable data - driven insights for public space planning and management. It demonstrates that machine learning can effectively identify and quantify key factors influencing public space use. As a result, it provides more accurate policy recommendations for urban planners and ensures that public space planning better meets the needs of different groups. For urban planners, the findings can guide the optimization of facility layouts for specific groups. For instance, adding canal cultural display nodes for cultural engagement groups and improving barrier - free facilities for groups with high accessibility needs, thereby enhancing the inclusiveness and utilization efficiency of public spaces.

ABSTRACT Through detailed analysis of protest movements in Spain and Egypt, this research examines how material elements – WiFi networks, urban furniture and physical barricades – gain political agency through network integration during urban resistance. Drawing on actor-network theory, the study analyses specific mechanisms through which infrastructure elements transition from passive objects to active political actors in digitally mediated protests. Results demonstrate how agency emerges where tactical innovations propagate across resistance networks, while digital platforms enable persistence through periods of suppression. These findings contribute to understanding material participation in urban protests while providing insights for movements operating under increasing algorithmic governance and surveillance.

Peneleh Village, the oldest settlement in Surabaya, is a heritage area rich in historical and architectural value, offering considerable potential as a cultural tourism destination in East Java. Within the scope of sustainable tourism development, accessibility is a crucial element for ensuring inclusivity, comfort, and equal opportunities for all visitors. This study investigates the current state of accessibility in Surabaya's Old Town through universal design, prioritizing usability, safety, and clarity in public spaces without discrimination. A qualitative descriptive method was adopted, incorporating field observations, in-depth interviews with local stakeholders and tourists, and a review of heritage planning documents and regulatory frameworks. Findings indicate that many infrastructure elements in Peneleh Village do not comply with universal design standards. Out of 35 assessed indicators, only 22.86% were fully implemented, 11.43% were partially implemented, and 65.71% were not implemented—highlighting a significant gap in accessibility provision. Key issues include uneven pedestrian pathways, inadequate visual signage, and a lack of inclusive public facilities. The study presents strategic recommendations to enhance accessibility and reposition Peneleh as a user-centered and inclusive heritage destination. Improving accessibility through universal design enriches visitor experience and contributes to more sustainable and equitable cultural tourism.

An innovative approach to organizing the monitoring of gas wells is considered, which involves the creation of an automated system with an emergency shutdown function for damaged loops. The main objective of the study is to improve the safety and reliability of gas production and underground gas storage facilities by promptly detecting malfunctions in well equipment and responding to potential emergencies in a timely manner. One option for implementing this method is to use a pneumometric approach. Pressure tubes act as sensitive elements, registering the dynamic pressure that arises as a result of gas flow around the tube. The measuring system determines the flow rate based on the difference between the total and static pressure, which allows the gas flow rate to be obtained. The results of modelling the dynamics of wells under various accident scenarios (when the trail breaks) have been analyzed, confirming the effectiveness of the proposed method. The system allows not only to respond quickly to the occurrence of defects, but also to prevent the development of emergency situations, which has a positive effect on the level of industrial safety and the environmental situation in the production area. The application of this approach may be relevant both for new buildings and for the modernization of existing facilities. The proposed monitoring method, thanks to a computer node that collects, processes and analyses data received from peripheral sensors in real time with the ability to automatically disconnect damaged loops , is an effective means of increasing the technological reliability of gas storage and gas production systems, significantly reducing the risks associated with gas leaks and emergencies. The system is designed with a modular structure, which makes it easy to adapt to different numbers of wells, change the topology or integrate with existing technological equipment without the need for complete reconstruction. The system is based on a combination of modern parameter control devices (pressure, temperature, gas flow) and signal logic processing modules that generate commands to shut down individual infrastructure elements in the event of abnormal situations.

Purpose This study investigates the relationship between five service quality dimensions: communication, courtesy, emotional support, hospital amenities and understanding of needs and the satisfaction of patient companions in Malaysian public hospitals during the COVID-19 pandemic. Design/methodology/approach This study employed a quantitative research approach, utilizing a structured questionnaire to survey 260 respondents in Malaysian public hospitals. The questionnaire was designed to assess respondents’ perceptions of service quality dimensions, measure their satisfaction with public hospital services and gather demographic and background information. The data underwent validation factor analysis to ensure the reliability and validity of the measurement model. Additionally, structural equation modeling (SEM) was conducted to evaluate the strength and significance of the relationships between the variables. Findings The study findings revealed that emotional support, courteous behavior, hospital amenities and responsiveness to companions’ needs in Malaysian public hospitals were positively associated with companion satisfaction. Additionally, communication was found to have a significant and negative impact on companion satisfaction. Originality/value By integrating emotional, behavioral and infrastructural elements into the SERVQUAL model, this study addresses the often-overlooked perspective of patient companions. It offers actionable insights for improving public hospital service quality in pandemic and post-pandemic contexts.

Research on AI has extensively considered biases related to gender and race. However, much less attention has been dedicated to another sociological tenet: that of class. Inspired by Bourdieu’s work on cultural stratification and distinction, this work sheds light on the sociocultural roots of artificial sociality, and on how these become manifest as ‘habitus’ within the outputs of generative AI models. We conducted 39 interviews with three AI chatbots – ChatGPT, Gemini and Replika – after asking them to impersonate individuals with different occupational positions: highly skilled professionals, blue-collar workers, university professors in the humanities, construction workers, computer scientists and hairdressers. Our qualitative study shows class-based regularities in how popular AI chatbots represent the lifestyle and tastes of fictional personas in artificial conversations, partly mediated by infrastructural and design elements. The article proposes a sociological perspective on bias in artificial sociality and experiments with interview methods in the study of generative AI.

The development of various types of innovation infrastructure (national, regional, sectoral) is particularly important for sustainable development, competitiveness and economic security in countries in the context of the transition to a new technological order and the digitalization of the economy. Innovation infrastructure supports innovation activity in a country and its regions. This issue is becoming increasingly relevant due to the volatility of the global economic system and the difficult geopolitical situation. The aim of this article is to analyze the features of Kazakhstan’s innovative infrastructure and provide recommendations for its further development. The article examines the essence, types, and elements of innovation infrastructure, based on a theoretical review, proving its importance for the innovative development of the country. It demonstrates the role of «hard» and «soft» infrastructure elements, using the example of international experience, and reveals the benefits of various methods for organizing them. The level of regional diversity in innovative development within Kazakhstan is explored, as well as the characteristics of national, regional, and sector-specific types of innovation infrastructures. A study revealed shortcomings in SEZ operations, and the need for clustering innovation activities was justified. Conclusions were drawn about the benefits and opportunities of existing special economic zones and technology parks for organizing clusters. The recommendations on improving the organization and state support for the long-term development of innovative infrastructure were substantiated for the country.

Estimate traffic cyclist crashes using Poisson-Tweedie models.

The article deals with the basic principles of reorganization of the territory of the Vinnytsia National Technical University (VNTU) in the context of modern urban, architectural, social and environmental challenges. Attention is focused on the need to create a multifunctional, inclusive and sustainable sports space, which is integrated into the structure of a university campus and meets the requirements of the student community.The current state of the object is analyzed: physical and moral wear of infrastructure elements, lack of zones for different sports, inaccessibility to low -mobility groups. The proposed concept involves dividing the territory into two levels with a clear functional zoning: football field, treadmills, gym, stands, recreation areas, skatepark, volleyball, basketball, tennis and badminonic platforms, as well as the introduction of "and implementation of the" signs.The importance of using innovative solutions-Smart-lighting, ecological materials, energy efficient technologies is emphasized. A structural analysis of project decisions on safety, comfort and social integration has been carried out. The reorganization of the territory of the stadium is positioned as a factor in the formation of a favorable environment for a healthy lifestyle, increasing the social activity of students and the positive image of the university.

BackgroundThe recognition of the unintended impact of COVID-19 mitigation measures to the availability of sexual and reproductive health (SRH) services led to the initiation of mitigation and health systems support mechanisms within public health facilities by the Ministry of Health (MoH) in Kenya to maintain pre-Covid-19 levels of SRH service provision. These recovery mechanisms however concentrated on policy and infrastructural elements of service provision with limited attention given to the psychosocial impacts of COVID-19 on health care workers (HCWs). This paper examines the psychosocial impact of COVID-19 on front line family planning (FP) and sexually transmitted infections (STI) management HCWs and their coping mechanisms with a view to suggesting ways in which HCWs can be supported during future pandemics.MethodologyThis paper employs a mixed methods approach with quantitative methodology analyzing data on the preparedness of the health sector to maintain service provision levels and qualitative data examining the mental and psychosocial states of HCWs who provide FP and STI health care services within Kenyan public health facilities.ResultsOur main finding was that the psychosocial wellbeing of HCWs was majorly neglected in the government response mechanisms for the pandemic leading to burnout and depression, as well as HCWs absconding their duties in the initial stages of the pandemic, and avoidance of testing and disclosure of status as the pandemic progressed. Some of these mechanisms undermined the mitigation measures by the government and put patients and colleagues at risk of infection by HCWs whose COVID-19 status remained unknown.ConclusionsWe recommend that future responses include mechanisms that address the psychosocial wellbeing of HCWs as a core element of the response for effective management of pandemics. In the case of new and unprecedented pandemics such as COVID-19, it is important that HCWs are provided with accurate and timely information about the pandemic as well as to what is expected of their conduct in service delivery and in the promotion of a culture of risk reduction.

This study examines the formation of social-ecological indicators among motor vehicle users related to pollutant emissions in Kuala Terengganu. Vehicle emissions are identified as one of the main contributors to urban air pollution; however, there is still a lack of comprehensive studies that integrate social and ecological aspects. This study employs the Social-Ecological Systems (SES) Framework to identify factors influencing user behavior, as well as related governance and infrastructure elements. A total of 11 informants were interviewed in a semi-structured manner, including users, government agency representatives, academic experts, and private industry representatives. Data were analyzed thematically based on codes derived from the SES framework. Initial findings indicate that factors such as user awareness, economic constraints, the effectiveness of existing policies, and access to green technology influence the formation of effective indicators. This study proposes several social-ecological indicators that local authorities can use to formulate more inclusive and community-based policies. These findings are expected to contribute to more sustainable carbon footprint management.

Medical imaging has developed from an auxiliary means of clinical examination into a significant method and intuitive basis for clinical diagnosis of diseases, providing all-around and full-cycle health protection for the people. The Internet of Medical Things (IoMT) allows medical equipment, intelligent terminals, medical infrastructure, and other elements of medical production to be interconnected, eliminating information silos and data fragmentation. Medical images disseminated in IoMT contain a wide diversity of sensitive patient information, which means protecting the patient's personal information is vital. In this work, an Adversarial-improved reversible steganography network (Airs-Net) for computed tomography (CT) images in the IoMT is presented. Specifically, the Airs-Net adopting the prediction-embedding strategy mainly consists of an image restoration network, an embedded pixel location network, and a discriminator. The image restoration network is effective in restoring the pixel prediction error of the restoration set in integer and non-integer scaled images of arbitrary size when information is concealed. The embedded information location network can automatically select pixel locations for information embedding based on the interpolated image features of the degraded image. The restored image, embedding location map, and embedding information are fed into the embedder for information embedding, and the subsequent secret-carrying image is continuously optimized for the quality of the information-embedded image by the discriminator. Quantitative results show that Airs-Net outperforms state-of-the-art methods in both PSNR and SSIM. Further, the qualitative and quantitative results and analyses under specific clinical application scenarios and in coping with multiple types of medical image information hiding demonstrate the excellent generalization performance and practical application capability of the Airs-Net.

Background: Telehealth incorporation is changing the nursing practice in cardiac primary care; technology-driven nursing interventions are providing innovative ways to improve patient outcomes and patient access to care. Nursing interventions driven by technology, such as remote patient monitoring, virtual consultations, and mHealth applications, are becoming increasingly important in cardiovascular disease management. Aim: This review aims to appraise the effectiveness, challenges, and future considerations for technology-driven nursing interventions in telehealth in the area of cardiac primary care, focusing on patient outcomes, nurse workload, and health equity. Methods: A scoping review was conducted using PubMed, CINAHL, Scopus, and Web of Science. The review included studies published between 2015 and 2025 through peer-reviewed journals. Inclusion criteria included studies utilizing a telehealth intervention with nurse involvement in cardiac primary care that had a qualitative/quantitative method. Data were synthesized thematically and quantitatively, based on the variability of outcomes in each study, which were summarized by patient health, nurses’ efficiency, and system-level. Results: The 50 studies showed telehealth interventions were reported to increase patient adherence (85% of studies), decrease hospital admissions (70% of studies), and increase nurse efficiency (60% of studies), but many studies did identify challenges, including digital literacy (40%) and infrastructure (30%). Secondly, reports on equity-related interventions demonstrated some success with providing healthcare to disadvantaged populations. Conclusion: While through technology-enhanced nursing telehealth intervention characteristics show large improvements in processes regarding cardiac care, a large investment in training, infrastructure, and other elements to address technology gaps may be necessary. Future research efforts should focus on implementing scalable and equitable strategies.

The article considers the basic principles of organizing the city's coastal areas using domestic and international design experience as an example. It describes the prerequisites for the formation of recreational spaces in coastal zones, as well as the methods and principles for designing infrastructure facilities. It analyzes the elements of the coastal area's infrastructure and substantiates the relevance of their use in organizing public spaces. It identifies their importance in forming the city's planning structure and their role in organizing a comfortable urban environment. It describes the principles of forming public spaces aimed at improving the environmental friendliness of natural objects in the urban environment.

Topicality. In the context of the rapid growth of the volume and importance of geospatial information, geographic information systems (GIS) are becoming an integral element of digital infrastructure, especially in critical industries such as transport, defense, energy, and healthcare. The relevance of the study is due to the need for a comprehensive understanding of architectural features, usage models, and risks associated with information security in modern GIS. The subject of the study is classification approaches to geographic information systems, their usage models, and the characteristic cybersecurity threats to which they are exposed. The study analyzed the key criteria for classifying GIS, reflecting both the technical aspects of building systems and the features of their application in applied tasks. Particular attention was paid to the connection of architectural models with vulnerabilities and attack vectors characteristic of each type of system. The purpose of the study is a comprehensive analysis of usage models and classification features of GIS from the point of view of information security, as well as the identification of effective protection mechanisms aimed at reducing cyber threats. As a result, a comparison of typical threats with GIS architectural models was carried out, and the most effective means of protection were also identified - from multi-factor authentication and network segmentation to the use of incident monitoring systems and cryptographic methods. Conclusions. The results of the study confirm the need to adapt security mechanisms to a specific architecture and model of GIS use. A comprehensive approach to classification, threat analysis and selection of protective measures allows significantly increasing the resilience of geographic information systems to cyberattacks and ensuring their safe operation in the conditions of digitalization and increasing technological risks.

This paper presents a procedural method aimed at protecting maritime critical infrastructure, which is essential for the functioning of developed nations. A novel approach, developed by the authors, is introduced—focusing on the behavioral analysis of vessels to enable early identification of suspicious maritime activity and to prevent damage or destruction to key infrastructure elements. An integrated system is proposed, combining real-time electronic surveillance with continuous access to and analysis of data from both national and international databases. Drawing inspiration from medical sciences, a screening-based methodology has been developed. Data on vessels collected from various sources are processed according to the criteria adopted by the authors, using a multi-criteria decision analysis (MCDA) approach. MCDA is a decision-support method that considers multiple criteria simultaneously. It allows for the comparison and evaluation of different options, even when they are difficult to compare directly. This characteristic is used to select high-risk vessels for further monitoring. An initial classification of a vessel as suspicious does not constitute proof of criminal activity but rather serves as a trigger for further coordinated actions. Data on vessels is collected from the AIS (automatic identification system) and platforms that store vessel history. The AIS is a powerful tool that processes parameters such as a ship’s speed and course. This article presents sample results from surveillance and pre-selection analyses using the AIS, followed by a multi-criteria assessment of the behavior of vessels identified through this process. The results are presented both graphically and numerically. The authors conducted several scenarios, analyzing different groups of vessels. Based on this analysis, recommendations were developed for the interpretation of the findings.

A key factor in successful military operations is proper reconnaissance of the theater of operations, which includes mapping transport infrastructures to ensure the accurate location of materials, troops, and supplies. The aim of this research is to facilitate the success of logistical reconnaissance using unmanned aerial vehicles to be able to get more accurate information of the state of transport infrastructure. Rail transportation is well suited to carry out this experiment. As a result of an empirical research, an extended visual checklist is defined, which can be used as a basis for investigating the parameters of the elements of the railway infrastructure, including operation possibilities. The elements of the list have been examined by drones and their effectiveness has also been verified. The three-dimensional (3D) model could be created based on the drone-records, provides information on the condition of the tracks and their surroundings. The drawn conclusions will be used to define general requirements for the use of unmanned aerial vehicles for logistical reconnaissance. The application of the presented methodology can significantly improve the effectiveness of military logistical reconnaissance.

Urban infrastructure, such as water supply networks, sewage systems, and electricity networks, is essential for the functioning of cities and, consequently, for the well-being of citizens. Despite its essentiality, the distribution of infrastructure in urban areas is not homogeneous, especially in cities in developing countries. Socially vulnerable areas often face significant deficiencies in sewage and road paving, exacerbating urban inequalities. In this regard, urban planners must consider the multiple elements of urban infrastructure and assess the compensation levels between them to reduce inequality effectively. In particular, the complexity of the problem necessitates considering the multidimensionality and heterogeneity of urban infrastructure. This complexity qualifies the operational framework of composite indicators as the natural solution to the problem. This study develops a new weighting system for the balanced expansion of urban infrastructures through composite indicators constructed by the Ordered Weighted Average operator. Implementing these weighting systems provides an opportunity to analyze urban infrastructure from different perspectives, offering transparency regarding the weaknesses and strengths of each perspective. This prevents unreliable representations from being used in decision-making and provides a solid basis for allocating investments in urban infrastructure. In particular, the study suggests that adopting weighting systems that prioritize intermediate values and avoid extreme values can lead to better resource allocation, helping to identify areas with deficient infrastructure and promoting more equitable urban development.