Blockchain and Machine Learning for Intelligent Multiple Factor-Based Ride-Hailing Services

One of the common transportation systems in Korea is calling taxis through online applications,which is more convenient for passengers and drivers in the modern area.However,the driver’s passenger taxi request can be rejected based on the driver’s location and distance.Therefore,there is a need to specify driver’s acceptance and rejection of the received request.The security of this systemis anothermain core to save the transaction information and safety of passengers and drivers.In this study,the origin and destination of the Jeju island SouthKorea were captured from T-map and processed based on machine learning decision tree and XGBoost techniques.The blockchain framework is implemented in the Hyperledger Fabric platform.The experimental results represent the features of socio-economic.The cross-validation was accomplished.Distance is another factor for the taxi trip,which in total trip in midnight is quite shorter.This process presents the successful matching of ride-hailing taxi services with the specialty of distance,the trip request,and safety based on the total city measurement.

Transportation Users’ Attitudes and Choices of Ride-Hailing Services in Two Cities with Different Attributes

The rapid technological developments in the 21st century created new opportunities for shared-use economy applications around the globe. Among other services, Transportation Network Companies (TNCs) like Uber and Lyft emerged in the US as a transportation alternative that offered a higher level of availability, reliability, and convenience than traditional modes. However, TNCs deployment was also blamed for increases in vehicle miles traveled (VMT) in large cities that embraced TNC services early on. Concerns about TNC adoption are also magnified by the current controversy in policy and legislation as to the regulation of TNCs. These new realizations create a need to examine the transportation users’ attitudes and perceptions regarding ride-hailing service, after nearly a decade of service in the Unites States market. In doing so, this paper compares and contrasts results from two recently completed studies aiming at creating links between socio-demographic factors and TNC use. The paper describes the methods employed to collect the data and presents findings from the analysis of 790 users’ responses in the Birmingham, AL and Miami Beach, FL markets. The study documents preferences and attitudes toward TNCs and highlights similarities and differences in travel behaviors related to local considerations. Moreover, the study uses the Least Absolute Shrinkage and Selection Operator (Lasso) method to identify predictors for TNC use based on the users’ responses in Birmingham and Miami Beach case studies. Vehicle availability and waiting time emerged as the only significant predictors for the Birmingham region whereas vehicle ownership, vehicle use, residency, and prior use of transit and TNC where some of the predictors identified for the Miami Beach area. Understanding the characteristics of TNC users and the leading reasons that drive people towards the use of TNCs services is expected to help transportation agencies and TNC providers in their efforts to plan for transportation services that meet customer needs in the future.

The social impact of ride-hailing services

Nowadays,sharing economy-based companies are gradually increasing their influence on our daily lives:we hire drivers on apps like Didi and Uber to pick us up instead of waiting for taxis.As P2P companies increase their influence in the public services sector,the government rationally diverts more of its attention towards regulating the quality and service of these companies.

How machine learning informs ride-hailing services:A survey

In recent years,online ride-hailing services have emerged as an important component of urban transportation system,which not only provide significant ease for residents’travel activities,but also shape new travel behavior and diversify urban mobility patterns.This study provides a thorough review of machine-learning-based methodologies for on-demand ride-hailing services.The importance of on-demand ride-hailing services in the spatiotemporal dynamics of urban traffic is first highlighted,with machine-learning-based macro-level ride-hailing research demonstrating its value in guiding the design,planning,operation,and control of urban intelligent transportation systems.Then,the research on travel behavior from the perspective of individual mobility patterns,including carpooling behavior and modal choice behavior,is summarized.In addition,existing studies on order matching and vehicle dispatching strategies,which are among the most important components of on-line ridehailing systems,are collected and summarized.Finally,some of the critical challenges and opportunities in ridehailing services are discussed.

Operational Characteristics of Paratransit Services with Ride-Hailing Apps in Asian Developing Cities: The Phnom Penh Case

Rapid adoption of ride-hailing apps (RHAs) has greatly influenced the way people travel—there is no exception for paratransit users. However, it remains unclear whether RHAs would be regarded as threats or opportunities among paratransit operators in Asian developing cities. While RHAs have been viewed as disruptive transportation, several studies explored the threats of RHAs on taxi industry—but only a few examined such threats on other paratransit services (e.g., auto-rickshaws). This study assessed the changes in the operational services among paratransit operators who have adopted RHAs. The changes were examined by statistical comparisons using data collected from questionnaire survey with 182 Bajaj drivers in Phnom Penh, January 23-27, 2018, as a case study. Results showed that majority of the interviewed drivers started new services with RHAs less than a year ago—they were younger (88%) satisfied with RHAs and acknowledged improvements on their operational services. The results suggested that RHAs would be opportunities for those paratransit drivers who have adopted them, while they would be threats for those who have not. The collected data serve as useful inputs for future public transport planning in Asian developing cities.

Debt,sleep deprivation and psychological distress among online ride-hailing drivers:evidence from China

An online ride-hailing driver(ORHD)refers to a driver who takes orders and provides rental car services to passengers via an online service platform.1 ORHD plays a significant role in the urban transport system worldwide,operating through many platforms.According to official data from the Chinese Ministry of Transport,a total of 1.6 million vehicle transport permits were issued by the end of March 2022.

Sharing Smart Services,Jointly Promoting Trade Development

In 2024,the China International Fair for Trade in Services (hereinafter referred to as CIFTIS) opened in the China National Convention Center and Shougang Park on September 12th.The theme of the CIFTIS this time was"global services,shared prosperity",which is not only a window for allowing the world to discover the development of China's service trade,but is also a bridge for promoting global cooperation with regards to the service trade.As one of the world-famous service trade events,the CIFTIS has become an important business card allowing China to open up.The CIFTIS has attracted the attention of the whole world and become a bridge for all parties to share development opportunities,promote industrial growth,and strengthen communication.

Residents’perceptions of ecosystem services in an urbanizing basin:A case study in the Guanting Reservoir basin,China

Understanding stakeholders’differences in perceptions of ecosystem services(ES)is crucial for guiding ecolog-ical conservation and planning.However,the variations of ES perception amongst different types of residents in urbanizing areas along an urban-rural gradient are still poorly understood.Combining a questionnaire-based survey,redundancy analysis,and statistical tests,we delineated the urban-rural gradient according to local res-idents’socio-economic characteristics,and investigated the differences in local residents’perceptions of ES and potential factors affecting them in the Guanting Reservoir basin,a rapidly urbanizing basin in China.The results showed that residents living in urban-rural transitional areas attached great importance to provisioning services of providing food and domestic water,regulating services of carbon sequestration and air purification,and cul-tural services of providing education and training,which were 0.7%-13.1%,0.7%-9.1%and 2.5%-21.2%higher than that of residents in other areas,respectively.Age and occupation were major factors affecting residents’perceptions.In terms of land-use types that deliver ES,the difference in perceptions of ES delivered by grassland was the greatest amongst residents.Our results support recommendations for policymakers to take into account the stakeholders’diverse perceptions,thus promoting residents’sense of gain on ES.

Healthcare Services Interoperability in Kenya: Challenges and Opportunities

In an attempt to assess the Kenyan healthcare system, this study looks at the current efforts that are already in place, what challenges they face, and what strategies can be put into practice to foster interoperability. By reviewing a variety of literature and using statistics, the paper ascertains notable impediments such as the absence of standard protocols, lack of adequate technological infrastructure, and weak regulatory frameworks. Resultant effects from these challenges regarding health provision target enhanced data sharing and merging for better patient outcomes and allocation of resources. It also highlights several opportunities that include the adoption of emerging technologies, and the establishment of public-private partnerships to strengthen the healthcare framework among others. In this regard, the article provides recommendations based on stakeholder views and global best practices addressed to policymakers, medical practitioners, and IT specialists concerned with achieving effective interoperability within Kenya’s health system. This research is relevant because it adds knowledge to the existing literature on how healthcare quality can be improved to make it more patient-centered especially in Kenya.

Spatiotemporal variations in ecosystem services and their trade-offs and synergies against the background of the gully control and land consolidation project on the Loess Plateau,China

Studying the spatiotemporal variations in ecosystem services and their interrelationships on the Loess Plateau against the background of the gully control and land consolidation(GCLC)project has significant implications for ecological protection and quality development of the Yellow River Basin.Therefore,in this study,we took Yan'an City,Shaanxi Province of China,as the study area,selected four typical ecosystem services,including soil conservation service,water yield service,carbon storage service,and habitat quality service,and quantitatively evaluated the spatiotemporal variation characteristics and trade-offs and synergies of ecosystem services from 2010 to 2018 using the Integrated Valuation of Ecosystem Services and Trade-offs(InVEST)model.We also analysed the relationship between the GCLC project and regional ecosystem service changes in various regions(including 1 city,2 districts,and 10 counties)of Yan'an City and proposed a coordinated development strategy between the GCLC project and the ecological environment.The results showed that,from 2010 to 2018,soil conservation service decreased by 7.76%,while the other three ecosystem services changed relatively little,with water yield service increasing by 0.56% and carbon storage service and habitat quality service decreasing by 0.16% and 0.14%,respectively.The ecological environment of Yan'an City developed in a balanced way between 2010 and 2018,and the four ecosystem services showed synergistic relationships,among which the synergistic relationships between soil conservation service and water yield service and between carbon storage service and habitat quality service were significant.The GCLC project had a negative impact on the ecosystem services of Yan'an City,and the impact on carbon storage service was more significant.This study provides a theoretical basis for the scientific evaluation of the ecological benefits of the GCLC project and the realization of a win-win situation between food security and ecological security.

Exploring the Spatiotemporal Changes and Driving Forces of Ecosystem Services of Zhejiang Coasts,China,Under Sustainable Development Goals

Ecosystem services(ESs)refer to the continuous provisioning of ecosystem goods and services that benefit human beings.Over recent decades,rapid urbanization has exerted significant pressure on coastal ecosystems,resulting in biodiversity and habitat loss,environmental pollution,and the depletion of natural resources.In response to these environmental challenges,the Sustainable Development Goals(SDGs)were proposed.Given the pressing need to address these issues,understanding the changes in ESs under the SDGs is crucial for formulating specific ecological strategies.In this study,we first analyzed land use and cover change in the Zhejiang coasts of China during 2000–2020.Then,we investigated the spatiotemporal configuration of ESs by integrating carbon storage(CS),soil retention(SR),habitat quality(HQ)and water yield(WY)using the Integrated Valuation of Ecosystem Services and Tradeoffs(InVEST)model.The driving mechanisms of ESs,which varied by space and time,were also explored using the Geo-detector method.The results revealed that,over the past two decades:1)the Zhejiang coasts have experienced a significant increase of 2783.72 km^(2) in built-up land areas and a continuous decrease in farmland areas due to rapid urbanization;2)owing to higher precipitation,extensive vegetation cover,and reduced anthropogenic disturbances,forests emerge as a crucial land use type for maintaining ecosystem services such as HQ,CS,WY,and SR;3)ESs have generally declined across the entire Zhejiang coasts,with a significant decrease observed in the northern areas and an increase in the southern areas spatially;4)the expansion of built-up land areas emerged as the primary factor affecting ecosystem services,while the vegetation factor has been increasingly significant and is expected to become predominant in the near future.Our study provides insights of understanding of ecosystem service theory and emphasizing the importance of preserving biodiversity for long-term sustainable development,and valuable scientific references to support the ecological management decision-making for local governments.

Regional Digital Financial Services Security Clinic for Asia Pacific Region

April 24-25, Seoul, Republic of Korea The International Telecommunication Union(ITU) is organizing the Regional Digital Financial Services Security Clinic for Asia Pacific Region on April 24-25, 2024 in Seoul, Republic of Korea. The event is being jointly held with FNSV Korea and the Korean Fintech Center.

ASTM provides world-leading digitalized standards services--Interview with Hu Yanan,Operation Manager of the ASTM International China Office

With a 126-year history,ASTM International still exudes strong vitality today.It is one of the most renowned standards organizations in the world,boasting a globally leading standards development system and database.It is open,transparent,fair,diverse,inclusive,and consensus-driven,but these are just some of its characteristics.ASTM always prioritizes the development of standards and the needs of industries and users.

Mapping ecosystem services in urban and peri-urban areas.A systematic review

Urban and peri-urban ecosystems are subjected to an intense impact.The demand for ecosystem services(ES)is higher in these areas.Nevertheless,despite the anthropogenic pressures,urban and peri-urban ecosystems supply important ES.Mapping is a crucial exercise to understand ES dynamics in these environments better.This work aims to systematically review mapping ES in urban and peri-urban areas studies,following the Preferred Reporting Items for Systematic Reviews and Meta-alpha Methods.A total of 207 studies were selected.The results show increased work between 2011 and 2023,mainly conducted in Europe and China.Most work were developed in urban areas and did not follow an established ES classification.Most studies focused on the ES supply dimension,the regulation and maintenance section.Regarding provisioning ES,most studies focused on Cultivating terrestrial plants for nutrition,regulating and maintainin g Atmospheric composition and conditions,and for cultural ES on Physical and experiential interactions with the natural environment.Quantitative methods were mostly applied following Indicator-based(secondary data:biophysical,socio-economic)models.Very few work validated the outputs.Several studies forecasted ES,primarily based on land use changes using CA-Markov approaches.This study provides an overview of the most mapped urban and peri-urban ES globally,the areas where more studies need to be conducted,and the methods developed.

GraphSTGAN:Situation understanding network of slow-fast high maneuvering targets for maritime monitor services of IoT data

With the rapid growth of the maritime Internet of Things(IoT)devices for Maritime Monitor Services(MMS),maritime traffic controllers could not handle a massive amount of data in time.For unmanned MMS,one of the key technologies is situation understanding.However,the presence of slow-fast high maneuvering targets and track breakages due to radar blind zones make modeling the dynamics of marine multi-agents difficult,and pose significant challenges to maritime situation understanding.In order to comprehend the situation accurately and thus offer unmanned MMS,it is crucial to model the complex dynamics of multi-agents using IoT big data.Nevertheless,previous methods typically rely on complex assumptions,are plagued by unstructured data,and disregard the interactions between multiple agents and the spatial-temporal correlations.A deep learning model,Graph Spatial-Temporal Generative Adversarial Network(GraphSTGAN),is proposed in this paper,which uses graph neural network to model unstructured data and uses STGAN to learn the spatial-temporal dependencies and interactions.Extensive experiments show the effectiveness and robustness of the proposed method.

Mapping Climate Services for Disaster Risk Management: A Systematic Review and Research Gaps from a Policy Process Perspective

Climate services (CS) are crucial for mitigating and managing the impacts and risks associated with climate-induced disasters. While evidence over the past decade underscores their effectiveness across various domains, particularly agriculture, to maximize their potential, it is crucial to identify emerging priority areas and existing research gaps for future research agendas. As a contribution to this effort, this paper employs the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology to review the state-of-the-art in the field of climate services for disaster risk management. A comprehensive search across five literature databases combined with a snowball search method using ResearchRabbit was conducted and yielded 242 peer-reviewed articles, book sections, and reports over 2013-2023 after the screening process. The analysis revealed flood, drought, and food insecurity as major climate-related disasters addressed in the reviewed literature. Major climate services addressed included early warning systems, (sub)seasonal forecasts and impact-based warnings. Grounded in the policy processes’ theoretical perspective, the main focus identified and discussed three prevailing policy-oriented priority areas: 1) development of climate services, 2) use-adoption-uptake, and 3) evaluation of climate services. In response to the limitations of the prevalent supply-driven and top-down approach to climate services promotion, co-production emerges as a cross-cutting critical aspect of the identified priority areas. Despite the extensive research in the field, more attention is needed, particularly pronounced in the science-policy interface perspective, which in practice bridges scientific knowledge and policy decisions for effective policy processes. This perspective offers a valuable analytical lens as an entry point for further investigation. Hence, future research agendas would generate insightful evidence by scrutinizing this critical aspect given its importance to institutions and climate services capacity, to better understand intricate facets of the development and the integration of climate services into disaster risk management.

A Hybrid Machine Learning Approach for Improvised QoE in Video Services over 5G Wireless Networks

Video streaming applications have grown considerably in recent years.As a result,this becomes one of the most significant contributors to global internet traffic.According to recent studies,the telecommunications industry loses millions of dollars due to poor video Quality of Experience(QoE)for users.Among the standard proposals for standardizing the quality of video streaming over internet service providers(ISPs)is the Mean Opinion Score(MOS).However,the accurate finding of QoE by MOS is subjective and laborious,and it varies depending on the user.A fully automated data analytics framework is required to reduce the inter-operator variability characteristic in QoE assessment.This work addresses this concern by suggesting a novel hybrid XGBStackQoE analytical model using a two-level layering technique.Level one combines multiple Machine Learning(ML)models via a layer one Hybrid XGBStackQoE-model.Individual ML models at level one are trained using the entire training data set.The level two Hybrid XGBStackQoE-Model is fitted using the outputs(meta-features)of the layer one ML models.The proposed model outperformed the conventional models,with an accuracy improvement of 4 to 5 percent,which is still higher than the current traditional models.The proposed framework could significantly improve video QoE accuracy.

Coupling Coordination Analysis of Cropland Intensification and Agroecosystem Services:Evidence from Loess Plateau in Shaanxi Province,China

One of the greatest challenges in the agroecosystem is to improve cropland intensification while preserving agroecosystem services.While many studies have investigated the effect of cropland intensification on agroecosystem service,the interactive coupling and coordination among these factors remain largely unexplored.In view of this,this study performed a case study of the Loess Plateau in Shaanxi Province,China and constructed comprehensive evaluation models to quantify the cropland intensification and agroecosystem service in this area.Balance analysis and the coupling coordination degree model were used to evaluate the interactive relationship between cropland intensification and agroecosystem service,and statistical analysis and spatial autocorrelation were used to analyze the spatial characteristics and potential mechanism of the coupling coordination.Results show that both the cropland intensification and agroecosystem service in the study area were relatively low yet gradually increased from 2000 to 2020.Agroecosystem service lag was identified as the dominant unbalanced development type.Improving the supply capacity of agroecosystem services plays a key role in the balanced development of cropland in the Loess Plateau.The coupling coordination degree between cropland intensification and agroecosystem service ranges from basic coordination to serious incoordination.Therefore,cropland intensification practices in the area should be optimized to enhance this coordination degree.An upward trend was also observed in the coupling coordination degree from2000 to 2020.The withdrawal of marginal cropland in the Grain for Green program is one of the most important reasons for this trend,especially for the northern region.Around 83.6%of the high-high clusters are concentrated in the southern region of the Loess Plateau,whereas 70.5%of the low-low clusters are distributed in the northern region.These clustering characteristics are mainly attributed to the environmental suitability of these areas for agriculture and their degree of economic development.

Which Neighborhoods Have Easier Access to Online Home Delivery Services?A Spatiotemporal Accessibility Analysis in Nanjing,China

The rise in online home delivery services(OHDS)has had a significant impact on how urban services are supplied and used in recent years.Studies on the spatial accessibility of OHDS are emerging,but few is known about the temporal dimension of OHDS accessibility as well as the geographic and socioeconomic differences in the spatiotemporal accessibility of OHDS.This study measures the spatiotemporal accessibility of four types of OHDS,namely leisure,fresh and convenient,medical,and catering services.The geographic and socioeconomic disparities in the spatiotemporal accessibility of these four types of OHDS are then identified using spatial statistical methods and the Kruskal-Wallis test(K-W test).The case study in Nanjing,China,suggests that:1)spatiotemporal accessibility better reflects the temporal variation of OHDS accessibility and avoids overestimation of OHDS accessibility when only considering its spatial dimension.2)The spatiotemporal accessibility of OHDS varies geographically and socioeconomically.Neighborhoods located in the main city or neighborhoods with higher housing prices,higher population density,and higher point of interest(POI)mix have better OHDS spatiotemporal accessibility.Our study contributes to the understanding of OHDS accessibility from a spatiotemporal perspective,and the empirical insights can assist policymakers in creating intervention plans that take into account variations in OHDS spatiotemporal accessibility.

The Digitization of Public Services and Its Contribution to the Quality of Service in Relation to User Satisfaction

In recent years, some governments have been working on solutions to transform public administrations and provide high-quality services to users. The United Nations has recommended integrating digital technology into various aspects of life, including public services. The objective is to offer real-time, high-quality digital services, improve the delivery of public services, enhance their effectiveness and efficiency, while achieving objectives such as transparency, interoperability and citizen satisfaction. However, most governments in developing countries are unable to keep up with this trend. As a result, they often create digital public services that fall short of users’ expectations. This study aims to identify the fundamental factors influencing the quality of service in relation to user satisfaction and to explore the relevance of digital technology in implementing this quality within Cameroon public administrations. To achieve this, we used a qualimetric research method, which included non-directive interviews, questionnaires, and structured observations. The results showed that the public services offered in our study environment did not meet users’ expectations. However, the study identified the fundamental aspects to be considered in providing quality public services connected to user satisfaction, as well as the strengths of digitization in achieving this quality.