State Of Infrastructure Research Articles

Assessment of plastic waste management in Bangladesh: A comprehensive perspective on sorting, production, separation, and recycling

The handling of plastic garbage has become a significant environmental and social issue worldwide, including in Bangladesh. This study thoroughly evaluates the methods used in Bangladesh for managing plastic trash, explicitly focusing on sorting, manufacturing, separation, and recycling. The research utilizes qualitative and quantitative methods, such as surveys, interviews, and analysis of existing data, to get insights into the present condition of plastic waste management infrastructure, policies, and practices in Bangladesh. This text examines the difficulties and advantages of categorizing plastic garbage, including the involvement of the informal sector and the absence of organized procedures. In addition, the research examines the manufacturing and consumption habits that contribute to the accumulation of plastic trash, emphasizing the necessity for sustainable alternatives and efforts to raise consumer awareness. The global mismanagement rate is 22%, and the recycling rate for plastic trash is 9%, which is lower. Six hundred forty-six metric tons of plastic waste are collected daily in Bangladesh, yet only 10% of that waste is recycled, and 37.2% needs to be correctly disposed of. Many techniques are utilized to recycle plastic trash worldwide, but Bangladesh wants to recycle 50% of plastic garbage by 2025. Moreover, the research investigates methods for separating plastic waste, highlighting adequate segregation's significance in streamlining recycling procedures. The process assesses current recycling activities and infrastructure, pinpointing any deficiencies and potential opportunities for enhancement. The analysis highlights the importance of improving recycling capability and advocating for circular economy concepts to reduce plastic pollution and prevent resource depletion. In summary, this comprehensive analysis of plastic waste management in Bangladesh provides significant insights for policymakers, industrial players, and civil society participants.

Evaluation of Sabo Infrastructure Using UAV/Drone Technology for Monitoring and Inspection Data (Case Study: Sabo Dam Bakalan, Cangkringan District, Sleman)

The sabo dam serves as a structure positioned along a river branch, intended to manage and contain sediment for either a temporary or permanent duration, functioning as a system to combat potential disasters caused by erosion and sedimentation. Given the significance of sabo infrastructure in mitigating sediment- related calamities, it is essential to uphold and advance these structures through continuous monitoring, necessitating timely access to detection data. However, the inspection and monitoring of sabo buildings present considerable challenges, including the extensive coverage area of the river and the difficulty in accessing various building locations.To address these challenges, alternative approaches are being employed for the inspection and monitoring of sabo buildings. One such approach involves the utilization of drone-based asset survey technology. This technology enables the recording of precise object geometries and the generation of structural information that can be validated on-site, particularly in the context of infrastructure conditions related to sabo dams. By integrating drone technology, it is anticipated that the process of inspecting and monitoring buildings and land areas surrounding sabo dams can be expedited, with increased precision and enhanced safety measures.

Development of a Framework to Improve the Provision of Water, Sanitation, and Hygiene in Healthcare Facilities of Mwandi District in Western Province

Healthcare facilities (HCFs) require safe water, sanitation, hygiene, environmental cleaning, and waste management (WASH) in the provision of quality services to promote, restore, maintain, and improve health. However, the unavailability of studies on the challenges and opportunities of WASH services in HCFs of Mwandi District has limited the potential for improved health care and quality of life. Without proper elucidation, this has the potency to dissuade women from using HCFs for childbirth and healthcare, potentially increasing maternal mortality rates. To examine the challenges and opportunities in accessing safe WASH services in HCFs in Mwandi District, more of Qualitative techniques were utilized to gather data from 8 HCFs in Mwandi District. This involved initial observations employing the WASH Status Checklist, followed by focus group discussions with expectant mothers and 23 key informant interviews. Thematic analysis was used to analyse the data. The results showed that only half of the investigated facilities provided basic water services, hampered by water salinity issues. Even though most facilities had improved sanitation facilities, they, however, do not meet the basic sanitation standards. This was primarily due to issues such as corroded pipes, insufficient accessible toilets for people with disabilities, and the absence of menstrual hygiene facilities. Many facilities lacked gender-segregated staff facilities. Most of the facilities had functional hand hygiene facilities but also did not meet the basic standards due to a lack of soap for hand washing. A significant number encounter inefficiencies in cleaning protocols, and the majority face poor infrastructure conditions. The findings further revealed that these challenges stem from inadequate prioritization and funding for Water, Sanitation, and Hygiene (WASH) initiatives. The existing knowledge often concentrates on individual components, the findings stress the necessity for an integrated approach that collectively addresses water supply, sanitation, hygiene, and waste management. This holistic perspective can significantly contribute to the development of more effective guidelines and policies, offering a nuanced understanding of the interconnected nature of WASH components. Furthermore, the research sheds light on the pivotal role of localized political will, specifically highlighting the influence of Health Centre Advisory Committees (HAHC) in shaping governance at the community level, especially concerning WASH projects. The study offers a comprehensive overview of challenges and sustainability opportunities related to WASH services, crucial for their effective functioning. It emphasizes the necessity for heightened awareness and increased budget allocation for the sustainable maintenance of WASH services

Policy governance in the plantation sector: Challenges and impacts of palm oil in Riau Province, Indonesia

This study aims to examine and challenge the impact of local government policy governance on the oil palm plantation sector in Riau Province, Indonesia. It was discovered that 1,628 million hectares of illegal oil palm plantations are located within forest areas. Plantation area and crop harvest areas are declining due to the increase in damaged old plants, low productivity of plantation crops, inadequate facilities and infrastructure conditions, low technology application, plantation business licensing, limited downstream plantation industry and marketing, assistance in changing the attitudes, behavior, and skills of farmers. The methodology used was exploratory qualitative to explore this topic, and the determination of research topics was conducted using Biblioshiny application analysis. Then, the data was analyzed using Nvivo 12 Plus software. The results of this study discovered that the policy governance of the oil palm plantation sector as a leading commodity in Riau Province, Indonesia, is influenced by three dimensions: firstly, the actor dimension; secondly, the structural dimension; and third, the empirical dimension of governance. This research contributes as a knowledge reference to oil palm plantations.

Pemanfaatan Media Animasi Pembelajaran Pada Materi Indahnya Kebersamaan Dengan Berjamaah Untuk Meningkatkan Kualitas Spiritual Siswa Kelas VII SMP Pelita Al-Qur’an Wonosobo

This research has the following objectives: 1) To find out about the concept of using PAI learning animation media as material about the beauty of togetherness in congregation in an effort to improve the spiritual quality of class VII students at Pelita Al-Qur'an Middle School; 2) To find out the implementation of learning material about the beauty of togetherness in congregation through the use of animation media as an effort to improve the spiritual quality of class VII students at Pelita Al-Qur'an Middle School, Wonosobo; 3) To determine the inhibiting and supporting factors in the use of PAI animation learning media in delivering beautiful material together with the congregation of class VII students at Pelita Al-Qur'an Middle School, Wonosobo.This research uses a qualitative field approach. The data sources used came from the principal of Pelita Al-Qur'an Middle School, PAI teachers and students. Data obtained using observation, interview and documentation techniques. Data analysis was carried out using data reduction, display and drawing conclusions.The results of this research show that: 1) The concept of using animated learning media refers to the character of students which is aimed at increasing their religious level, curiosity, respect for achievement, friendly or communicative, likes to read, independent, disciplined and responsible. 2) Implementation of learning with animation media in terms of material content using a forward flow, in terms of time allocation using animation media in collaboration with other media, in terms of types of animation media used, including material videos, practice videos, material song videos and story videos. exemplary story. 3) The supporting factors for implementing this media in general are that it is more interesting so that students' motivation, understanding of the material and spiritual level can easily increase, while the obstacles are the lack of infrastructure, power outages and noisy environmental conditions because they are close to the main road.

Pengaruh Aksesibilitas Jalan Ende – Nuabosi Terhadap Peningkatan Perekonomian Masyarakat Kecamatan Ende

Nuabosi is one of the villages in the Ende District area, where this village helps improve the economy of Ende District in terms of meeting economic needs, namely in the form of various agricultural and plantation products. However, even though Nuabosi Village is sufficient to meet the economic needs of Ende District, distance and inadequate infrastructure conditions are some of the factors that influence the level of accessibility in Ende District. This research aims to determine the value and level of accessibility in the villages of Ende District. The accessibility measuring parameter data used is travel time, road pavement conditions, supporting facilities, and travel rates or costs. Data analysis uses quantitative descriptive analysis and crosstab analysis methods, using the total accessibility calculation formula. The results of the analysis based on a review of accessibility parameters and crosstabs show that the highest accessibility value for each village is Ria Raja Village with a value of 2.18 and the lowest is Tina Bani Village with a value of 0.37. The average level of accessibility in Ende District as a whole is 0.83, indicating a high level of accessibility, where the existing road conditions can influence the improvement of the economy of the people in Ende District. Crosstab analysis also shows that most of the factors determining accessibility are related to the socio-economic conditions of the community.

PERSEPSI PENGUNJUNG TERHADAP DAYA TARIK WISATA MANGROVE SETAPUK DI KOTA SINGKAWANG

Setapuk Mangrove tourism has the potential to be developed into natural tourism because it has the potential in the form of natural scenery, rainbow bridges and mangrove areas with various attractions and tourism infrastructure. The purpose of the study was to explain the perception and satisfaction of visitors to the attractiveness of Setapuk Mangrove tourism through available facilities. The method used a survey with 50 visitors as research informants selected by accidental sampling. Data collection was conducted through observation and interviews using a list of questions. Data analysis was carried out in a qualitative descriptive manner. Visitors' perception of the Setapuk Mangrove tourism area feels interested and quite satisfied with tourist objects in the form of natural scenery, flora, fauna, beaches, rivers and roads/tracks. It is also supported by the condition of facilities, cleanliness, comfort, safety and satisfaction of visitors as well as the physical condition of tourist facilities and infrastructure that are available or well maintained. It is supported by several tourism activities that get satisfied assessments by visitors, namely when observing mangrove beaches by speedboat. Accessibility conditions that are not supportive and physical conditions of infrastructure that are not good are basically weaknesses as well as advantages, because accessibility in muddy conditions will get more attention from visitors/researchers with educational purposes that require elements of unity with nature so that these conditions remain original, so this area has potency for ecotourism

Post-traumatic growth in later-life cognitive function? Evidence from the 1976 Great Tangshan Earthquake.

This study aimed to explore the long-term impacts of exposure to earthquake in adolescence on later-life cognitive function in China. Data were from the 2015 China Health and Retirement Longitudinal Study (CHARLS). Our analytical sample comprised 4394 participants aged 49 to 78 from two birth cohorts born between 1937 and 1966: exposed cohort during adolescence (born between 1952 and 1966), and non-exposed cohort during adolescence (born between 1937 and 1951). We defined earthquake exposure as the exposure severity of the 1976 Great Tangshan Earthquake (GTE). We selected community environmental characteristics as our key moderators. A difference-in-differences (DID) method was employed to estimate the long-term impact of the GTE on later-life cognitive function. We found that exposure to the earthquake during adolescence resulted in higher scores of later-life cognitive function (for males: β = 2.18; 95% CI: 0.70-3.66; for females: β = 1.22; 95% CI: 0.11-2.33). For males, this impact was moderated by community environmental characteristics including the old-age allowance program (β = 3.07; 95% CI: 1.94-4.19) and the condition of basic community infrastructures (β = 1.52; 95% CI: 0.84-2.19). Our study supports the post-traumatic growth theory. This finding suggest that individuals with early-life traumatic exposure need to be focused on. Additionally, improving the conditions of community infrastructures and establishing a community environment with comfort and security may be pretty important for promoting cognitive function and post-traumatic growth.

Analysis of variables to determine their influence on renewable energy forecasting using ensemble methods

Forecasting is of great importance in the field of renewable energies because it allows us to know the quantity of energy that can be produced, and thus, to have an efficient management of energy sources. However, determining which prediction system is more adequate is very complex, as each energy infrastructure is different. This work studies the influence of some variables when making predictions using ensemble methods for different locations. In particular, the proposal analyzes the influence of the aspects: the variation of the sampling frequency of solar panel systems, the influence of the type of neural network architecture and the number of ensemble method blocks for each model. Following comprehensive experimentation across multiple locations, our study has identified the most effective solar energy prediction model tailored to the specific conditions of each energy infrastructure. The results offer a decisive framework for selecting the optimal system for accurate and efficient energy forecasting. The key point is the use of short time intervals, which is independent of type of prediction model and of their ensemble method.

Anomaly Detection in Railway Sensor Data Environments: State-of-the-Art Methods and Empirical Performance Evaluation.

To date, significant progress has been made in the field of railway anomaly detection using technologies such as real-time data analytics, the Internet of Things, and machine learning. As technology continues to evolve, the ability to detect and respond to anomalies in railway systems is once again in the spotlight. However, railway anomaly detection faces challenges related to the vast infrastructure, dynamic conditions, aging infrastructure, and adverse environmental conditions on the one hand, and the scale, complexity, and critical safety implications of railway systems on the other. Our study is underpinned by the three objectives. Specifically, we aim to identify time series anomaly detection methods applied to railway sensor device data, recognize the advantages and disadvantages of these methods, and evaluate their effectiveness. To address the research objectives, the first part of the study involved a systematic literature review and a series of controlled experiments. In the case of the former, we adopted well-established guidelines to structure and visualize the review. In the second part, we investigated the effectiveness of selected machine learning methods. To evaluate the predictive performance of each method, a five-fold cross-validation approach was applied to ensure the highest accuracy and generality. Based on the calculated accuracy, the results show that the top three methods are CatBoost (96%), Random Forest (91%), and XGBoost (90%), whereas the lowest accuracy is observed for One-Class Support Vector Machines (48%), Local Outlier Factor (53%), and Isolation Forest (55%). As the industry moves toward a zero-defect paradigm on a global scale, ongoing research efforts are focused on improving existing methods and developing new ones that contribute to the safety and quality of rail transportation. In this sense, there are at least four avenues for future research worth considering: testing richer data sets, hyperparameter optimization, and implementing other methods not included in the current study.

Single-industry cities: social aspects of urban planning policy (as exemplified by the gold-mining city Bodaibo, Irkutsk region)

The article raises the issue of Russian single-industry cities, the social situation and social policy in the city as part of urban planning policy. The main attention is paid to the analysis of the situation at the single-industry cities: social aspects of urban planning policy (as illustrated by the gold-mining city of Bodaibo, Irkutsk region). More than 60 % of the city population is directly or indirectly connected with the gold mining industry. Consequently, Bodaibo can be considered as a single-industry gold-mining city that requires attention from the authorities and a special approach to the urban policy development. The relevance of the study is explained by the fact that there are no systematic comprehensive (including sociological) studies on gold mining cities and settlements in Russia. Purpose of the study: studying the needs of residents of the city of Bodaibo to improve the quality of life in terms of solving social problems and developing proposals to determine the directions of urban planning policy. Research results: in October 2022, the authors of the article conducted a sociological survey of the city Bodaibo residents to identify the satisfaction of citizens with living and working conditions, and to assess the comfort of the environment. It was found that the social conditions in the city are deteriorating: 30 % of citizens noted the quality of life as the worst, more than 60 % of respondents rated the state of social infrastructure as unsatisfactory. Conclusions: weaknesses in the city urban planning policy - lack of comfortable housing, high prices for rental housing for newcomers, poor condition of transport infrastructure, low quality of medical and cultural services. Due to the unresolved social problems, part of the population is leaving the city, the demographic situation is deteriorating. The authors analyzed studies on single-industry towns in other regions of the Russian Federation, got acquainted with the proposed models for solving urgent problems, also relying upon foreign experience. Based on the sociological survey results and acquaintance with the developed concepts for the reorganization of single-industry towns, the authors proposed some steps to improve the urban planning policy in the city of Bodaibo

Optimization Modeling for Pandemic Vaccine Supply Chain Management: A Review and Future Research Opportunities.

During various stages of the COVID-19 pandemic, countries implemented diverse vaccine management approaches, influenced by variations in infrastructure and socio-economic conditions. This article provides a comprehensive overview of optimization models developed by the research community throughout the COVID-19 era, aimed at enhancing vaccine distribution and establishing a standardized framework for future pandemic preparedness. These models address critical issues such as site selection, inventory management, allocation strategies, distribution logistics, and route optimization encountered during the COVID-19 crisis. A unified framework is employed to describe the models, emphasizing their integration with epidemiological models to facilitate a holistic understanding. This article also summarizes evolving nature of literature, relevant research gaps, and authors' perspectives for model selection. Finally, future research scopes are detailed both in the context of modeling and solutions approaches.

Data Management System - Water Supply and Channeling with GIS Mapping

GIS mapping enables visualizing spatial data related to water sources, distribution networks, infrastructure assets, and other pertinent information crucial for effective management. Asset management functionalities enable tracking the condition, maintenance schedules, and lifecycle of water infrastructure assets, ensuring optimal utilization and performance. This paper presents the design and implementation of an integrated data management system tailored for water supply and channeling, augmented with Geographic Information System (GIS) mapping capabilities. The system aims to streamline the management of water resources, optimize distribution networks, and enhance decision making processes for water utility providers and stakeholders. The system architecture comprises several key components: GIS mapping, data collection mechanisms, database management, sensor integration, network analysis tools, asset management functionalities, decision support systems, remote monitoring and control capabilities, and user interfaces. Data collection mechanisms encompass various sources such as sensors, surveys, satellite imagery, and existing databases to gather comprehensive datasets on water sources, quality parameters, infrastructure condition, and demographic factors. A robust database management system is employed to efficiently store, manage, and secure the collected data, facilitating easy retrieval and analysis. Real-time sensor data from water meters, flow meters, and pressure sensors are integrated into the system to provide insights into water usage patterns, network performance, and system health. Network analysis tools utilize GIS capabilities to optimize the layout of distribution networks, identify areas for expansion, and improve operational efficiency Remote monitoring and control capabilities empower operators to monitor and manage water systems from a centralized location, enabling proactive maintenance, leak detection, and emergency response. Security measures are implemented to safeguard sensitive water infrastructure data against unauthorized access, cyber threats, and data breaches, ensuring the integrity and confidentiality of the system. Overall, the integrated data management system presented herein offers a comprehensive solution for optimizing water supply and channeling operations, enhancing efficiency, reliability, and sustainability while minimizing costs and environmental impact

Prediction of Degraded Infrastructure Conditions for Railway Operation.

In the railway sector, rolling stock and infrastructure must be maintained in perfect condition to ensure reliable and safe operation for passengers. Climate change is affecting the urban and regional infrastructure through sea level rise, water accumulations, river flooding, and other increased-frequency extreme natural situations (heavy rains or snows) which pose a challenge to maintenance. In this paper, the use of artificial intelligence based on predictive maintenance implementation is proposed for the early detection of degraded conditions of a bridge due to extreme climatic conditions. For this prediction, continuous monitoring is proposed, with the aim of establishing alarm thresholds to detect dangerous situations, so restrictions could be determined to mitigate the risk. However, one of the main challenges for railway infrastructure managers nowadays is the high cost of monitoring large infrastructures. In this work, a methodology for monitoring railway infrastructures to define the optimal number of transductors that are economically viable and the thresholds according to which infrastructure managers can make decisions concerning traffic safety is proposed. The methodology consists of three phases that use the application of machine learning (Random Forest) and artificial cognitive systems (LSTM recurrent neural networks).

Attitudes of Parents of Children With Special Needs Towards Inclusive Education

Inclusive education is very important for all children especially for those with special needs. In the Republic of Kosovo, the inclusion it is an approach in progress. This study aimed to explore the attitudes of parents of children with special needs towards inclusive education. The current findings of inclusiveness, challenges, risks, benefits and achievements of inclusive education in the Kosovo education system were also analysed. Through a semi-structured interview, ten parents whose children attend regular classes in various schools in pre-university education in Kosovo were interviewed. The results of the research indicate that parents of children with special needs have similar attitudes towards inclusion. In their opinion, it should occur, but they are worried about the challenges that appear. Inclusion is seen as a good opportunity, capacity building, equality, socialization and part of the overall development of the child. Parents recommend improvements in infrastructure conditions and human resources for successful inclusion.

Sustainable procurement of medical devices in an international context - Part 3

Background and Objectives This article is the third in a series of three manuscripts published in this journal. It aims to describe how sustainable procurement of medical devices (MDs) can be implemented in operational projects in the context of developing countries. It also further details how the biomedical/clinical engineer lead (BCEL) in charge of technical support during the MD procurement process can apply sustainability principles and concepts of value-based procurement. Material and Methods Based on the authors’ experience of more than 20 years in procurement projects and implementation of MDs, the role of the BCEL will be developed from a theoretical point of view with the description of the second and third pillars of a sustainable purchase following the needs assessment: the assessment of existing conditions along with local capacities and the evaluation of the use conditions during the lifetime of the medical equipment. The application of these principles in operational projects will be further discussed by analyzing literature and lessons learned from projects implemented in developing countries. Results/Proposal The BCEL has a key role in the sustainable procurement of MDs to design the technical specifications of the goods, related services, and post-sales conditions to maximize the benefit of the investment. As the specialist can analyze the local existing conditions and capacities while ensuring efficient use of the MDs during their lifespan, they can contribute to a sustainable implementation of MDs in developing countries. The BCEL shall also be able to analyze the local and international markets to find all possible technological solutions that meet the needs, local conditions, and capacities and ensure quality use during the lifespan of the purchased MD. The BCEL shall have competencies in identifying all the risks related to the use of the MD from the safety risks linked to its installation, use, and maintenance to the sustainability risks linked to obtaining the conditions that guarantee the use of the device and maintaining them as long as possible. Examples of these conditions include the presence of qualified and trained users, availability of maintenance and consumable budgets, availability and maintenance of infrastructure conditions (access, electrical power, water, drainage, medical gasses, etc.), and last but not least, presence of patients requiring a diagnosis or treatment using the purchased MD who were identified during the evaluation of the first pillar: a sound needs assessment. Conclusion As an evolution of the BCEL’s traditional biomedical and clinical engineering work, he/she shall assume the responsibility to guarantee the sustainability of the MD purchase. This quality assurance and control role is achieved by a sound theoretical background knowledge based on the three sustainable procurement pillars: the needs, existing and lifetime use conditions assessments, the analysis of the local and international markets, and a broad understanding of sustainability risks.

Working Capital Management and Financial Performance of Small and Medium-Sized Enterprises (SMEs) and SACCOS in Kenya

Small and medium-sized enterprises (SMEs) play a critical role in driving economic growth, creating employment opportunities and promoting local revenue generation in Kenya. However, they face various challenges such as limited financial resources, inadequate infrastructure and volatile market conditions. Effective working capital management (WCM) is essential for SMEs to overcome these obstacles and achieve sustainable success. The aim of this research is to examine the impact of WCM on the financial performance of SMEs in Kenya. This paper uses literature review methodology to draw conclusions. The literature review provides insights from various studies that highlight the importance of credit management and internal factors that influence organizational performance. An efficient WCM is crucial for ensuring the financial stability of companies, especially SMEs. Poor WCM can lead to financial challenges and possible bankruptcy, while effective management can significantly increase financial efficiency. WCM involves monitoring a company's current assets and liabilities to ensure timely commitments while minimizing associated costs. This research contributes to understanding the importance of WCM for SMEs in Kenya and provides stakeholders with practical insights to improve financial performance through effective WCM strategies tailored to the Kenyan context.

Digital Currencies: Is Africa Ready?

Digital currencies are likely to modify the way businesses, people and governments transact in Africa. Nonetheless, several factors need to be assessed before the wide adoption of digital currencies in the continent. These factors include the regulatory environment for fintech, the condition of digital infrastructure and the degree of financial inclusion. This paper assesses the readiness of African countries for the issuance of digital currencies. The paper gives an overview of the African countries that have implemented or are considering implementing digital countries. It discusses the issues to be considered for a conducive environment to launch digital currencies. It explores the opportunities and challenges of developing and issuing digital currencies in Africa. The paper finds that although the developed mobile money network infrastructure, high mobile money penetration, the growth of the digital economy and high degrees of financial exclusion position Africa well for the adoption of central bank digital currencies (CBDCs), several challenges need to be addressed. These encompass lower levels of financial inclusion, digital exclusion, the digital divide, poor digital infrastructure and regulatory uncertainty. The paper provides recommendations for improving the prospects of digital currencies in Africa. These include the creation of a legal and regulatory framework for digital currencies, investing in digital infrastructure, improving internet connectivity and educating citizens on digital currencies. Digital currencies can lead to improved economic growth, increase cross border payments, promote financial inclusion and sustainable development Keywords: Africa, Digital Currencies, Digital Infrastructure, Financial Inclusion, legal, regulatory environment

AI competitions as infrastructures of power in medical imaging

ABSTRACT This article examines how platform-based AI competitions structure power relations in medical imaging research. It focuses on two leading platforms, Kaggle and Grand Challenge, which provide organisational as well as infrastructural support to run AI competitions. In dialogue with critical AI and platform studies research, we investigate how such competitions are organised – under which infrastructural conditions and by whom – and how this shapes processes of model production and evaluation. To address these concerns, we have collected data from 118 medical image AI competitions on Kaggle and Grand Challenge, organised between January 2017 and May 2022. In addition, a variety of platform boundary resources – platform documentation, competition descriptions, dataset descriptions, and competition leaderboards – have been gathered. The analysis of these materials shows, first, that platforms direct the AI development process by requiring substantial financial resources, defining which institutions can host a competition and under which conditions. Second, competition organisers define dataset diversity and the generalisability of models. As most datasets are constructed with data from hospitals in North America, Western Europe and China, the application of models to different geographical contexts is potentially limited. Finally, competition participants influence model development through the institutional, demographic, and disciplinary contexts in which they operate. Overall, the examination demonstrates the importance of critically interrogating the entire medical AI research pipeline, including the definition of research problems, the construction of datasets as well as model production and evaluation.

Human-Centric AI : Enhancing User Experience through Natural Language Interfaces

AI has significantly altered the way humans interact with technology. It is important to observe the impact of Natural Language Interfaces (NLIs) on user experiences in Human-Centric AI across various industries. Therefore, we specifically focus on the influence of Human-Centric AI and user interactions within AI chatbots in the United Arab Emirates (UAE). The aim of this study is to assess the factors that influence the acceptance of AI, examine its practical implications across different industries, and offer valuable insights for the responsible development of AI. A quantitative survey methodology was employed, involving 230 participants in the UAE. The research design, data collection, and analysis followed the Unified Theory of Acceptance and Use of Technology (UTAUT) model, which emphasizes performance expectancy, effort expectancy, social influence, and facilitating conditions. The survey encompassed a variety of participants from various organizations, with a majority expressing positive attitudes towards AI chatbots. The survey found that 80% of users agreed that AI systems improve task efficiency, 84% believe they help achieve goals, and 84% view them as practical. According to 75% of participants, the social impact is strongly influenced by AI chatbot system adoption. However, 80% understood the relevance of organizational infrastructure and favorable conditions. In particular, 72% of users stated that Natural Language Interfaces transform, indicating satisfactory user experiences. These features demonstrate the influence of Human-Centric AI adoption and its use in different organizations. Natural language interfaces play a critical role in improving human-centered AI user experiences, investigating theoretical issues and real-world applications, and providing guidance for the ethical use of AI.