Configuration Of Infrastructure Research Articles

Demand Time Series Prediction of Stacked Long Short-Term Memory Electric Vehicle Charging Stations Based on Fused Attention Mechanism

The layout and configuration of urban infrastructure are essential for the orderly operation and healthy development of cities. With the promotion and popularization of new energy vehicles, the modeling and prediction of charging pile usage and allocation have garnered significant attention from governments and enterprises. Short-term demand forecasting for charging piles is crucial for their efficient operation. However, existing prediction models lack a discussion on the appropriate time window, resulting in limitations in station-level predictions. Recognizing the temporal nature of charging pile occupancy, this paper proposes a novel stacked-LSTM model called attention-SLSTM that integrates an attention mechanism to predict the charging demand of electric vehicles at the station level over the next few hours. To evaluate its performance, this paper compares it with several methods. The experimental results demonstrate that the attention-SLSTM model outperforms both LSTM and stacked-LSTM models. Deep learning methods generally outperform traditional time series forecasting methods. In the test set, MAE is 1.6860, RMSE is 2.5040, and MAPE is 9.7680%. Compared to the stacked-LSTM model, MAE and RMSE are reduced by 4.7%and 5%, respectively; while MAPE value decreases by 1.3%, making it superior to LSTM overall. Furthermore, subsequent experiments compare prediction performance among different charging stations, which confirms that the attention-SLSTM model exhibits excellent predictive capabilities within a six-step (2 h) window.

Optimal Vehicle Scheduling and Charging Infrastructure Planning for Autonomous Modular Transit System

Prioritizing the development of public transport is an effective way to improve the sustainability of the transport system. In recent years, bus passenger flow has been declining in many cities. How to reform the operating mode of the public transportation system is an important issue that needs to be solved. An autonomous modular bus (AMB) is capable of physical coupling and uncoupling to flexibly adjust vehicle capacity as well as provide high-quality service under unbalanced passenger demand conditions. To promote AMB adoption and reduce the operating cost of the bus route, this paper presents a joint optimization method to simultaneously determine the AMB dispatching plan, charging plan, and charging infrastructure configuration scheme. Then, a mixed-integer programming model is formulated to minimize the operating costs of the bus route. A hybrid intelligent algorithm combining enumeration, cloning algorithm, and particle swarm optimization algorithm is designed to resolve the formulated model. Subsequently, an actual bus route is taken as an example to validate the proposed method. Results indicate that the developed method in this paper can reduce the operating costs and operational energy consumption of the route compared with the real route operating plan. Specifically, the reduction ratio of the former is 23.85%, and the reduction ratio of the latter is 5.92%. The results of this study validate the feasibility and advantages of autonomous modular transit service, contributing positively to the sustainable development of the urban public transportation system.

Software Development of an Integrated Water Management Optimisation Model: the Roy Hill Mine Case Study Application

AbstractThis case study utilizes data from the Roy Hill iron ore mine, which has a daily water balance of abstraction, use, and surplus disposal, to address the problem of water management prediction at a global level by analysing the results of each modelling task and evaluating the presence of potential critical scenarios with an automated, mathematically rigorous tool. This paper describes the development of a software application that aggregates the results of the various water management models built for each task and provides the optimal utilisation of water to minimise water disposal and thereby maximise water usage. The business benefits of this work include the ability to calculate the net present cost (NPC) for new water infrastructure configurations in an integrated way. Investing in capital projects for water management and evaluating various scenarios helps determine the optimal water infrastructure configuration, minimizing operational impact. Traditionally, water has not been viewed as a significant cost; however, the cost of water infrastructure is now one of the highest business investments in the mining industry of the Pilbara region of Western Australia. Introducing the concept of NPC for water in the mining industry is a novel approach to making informed decisions on water expenses and investments. The key to success lies in using automated modelling to achieve the most efficient environmental and operational balance. This approach reduces individual decision-making and leads to a more cost-effective and beneficial production outcome.

A novel socio-economic-environmental model to maximize prosumer satisfaction in smart residential complexes

As the adoption of distributed and renewable energy resources helps consumers evolve into prosumers who generate and trade their own energy, optimizing distributed renewable energy resources, electric vehicles, and energy storage in smart residential complexes is crucial to enhance satisfaction and capitalize on their potential for environmental and economic benefits. Nonetheless, limited progress has been made to quantify the impact of prosumer and energy manager preferences and the integrated socio-economic-environmental dynamics on energy scheduling and stakeholder satisfaction within smart communities. This study aims to overcome this challenge by proposing a socio-economic-environmental optimization model based on a preference-oriented management approach, which quantifies the impact of energy scheduling on stakeholder satisfaction in smart communities. The model inputs include infrastructure configurations, energy consumption patterns, and weather data. The simulation method includes the application of deep learning and System Advisor Model software in predicting weather conditions and photovoltaic and wind turbine systems energy generation. The simulation results are then imported as parameters in GAMS software to optimize the stakeholder satisfaction using CPLEX solver. Quantitative results show that with the simultaneous use of electric vehicles and energy exchange between energy communities, the highest level of satisfaction of the stakeholders in the smart grid including energy communities has been achieved at hour 24 and at the rate of 0.99 per-unit. The model reveals notable enhancements in stakeholder satisfaction, particularly through the integration of electric vehicles and energy trading in smart grids. It underscores the critical impact of aligning renewable energy strategies with prosumer socio-economic-environmental preferences, offering valuable insights for energy managers, policymakers, and community planners in fostering efficient, community-oriented smart grid systems.

A distributed tracing pipeline for improving locality awareness of microservices applications

AbstractThe microservices architectural style aims at improving software maintenance and scalability by decomposing applications into independently deployable components. A common criticism about this style is the risk of increasing response times due to communication, especially with very granular entities. Locality‐aware placement of microservices onto the underlying hardware can contribute to keeping response times low. However, the complex graphs of invocations originating from users' calls largely depend on the specific workload (e.g., the length of an invocation chain could depend on the input parameters). Therefore, many existing approaches are not suitable for modern infrastructures where application components can be dynamically redeployed to take into account user expectations. This paper contributes to overcoming the limitations of static or off‐line techniques by presenting a big data pipeline to dynamically collect tracing data from running applications that are used to identify a given number of microservices groups whose deployment allows keeping low the response times of the most critical operations under a defined workload. The results, obtained in different working conditions and with different infrastructure configurations, are presented and discussed to draw the main considerations about the general problem of defining boundary, granularity, and optimal placement of microservices on the underlying execution environment. In particular, they show that knowing how a specific workload impacts the constituent microservices of an application, helps achieve better performance, by effectively lowering response time (e.g., up to a reduction), through the exploitation of locality‐driven clustering strategies for deploying groups of services.

Energy Poverty and the Proliferation of Heterogeneous Infrastructure Configurations in Accra: Implications for Urban Energy Governance in African Cities

Energy Poverty and the Proliferation of Heterogeneous Infrastructure Configurations in Accra: Implications for Urban Energy Governance in African Cities

Sanitation configurations in Lilongwe: Everyday experiences on and off the grid

Scholars have called for increased attention to the practices through which residents of southern cities create and use infrastructure. The failures and disruptions of many particular artefacts have meant that people often develop multiple ways to access water, electricity, or transportation, even if all of them have limitations. For sanitation, thinking through heterogeneous infrastructure configurations can help us to see connections between toilets, and the reasons for maintaining access to different types of toilets, given their different risks and benefits. In this paper, we focus on plots in Lilongwe with both indoor flush-toilets and backyard latrines, and the lived experiences of people as they navigate choices about the use of these toilets. The presence of on and off-grid toilets is rooted in colonial urban form, yet is perpetuated – and proliferates in new places – as residents face a number of constraints, including most recently recurrent water shortages due to droughts. We consider both how this configuration challenges official imaginaries of urban sanitation, and how it helps residents to address different risks and sanitation needs. Drawing on the experience of Lilongwe, we reflect on what can be learnt from this heterogeneous infrastructural configuration in terms of planning for more resilient water and sanitation services in Global South cities and beyond.

Yeni İnşa Edilen Akıllı Şehirlerin Mekânsal Sürdürülebilirliği Verimliği için Yenilikçi Uygulamalar

The main objective of this study is to examine innovative policies and practices in the context of the sustainability of newly constructed smart cities. The efficiency of these settlements is also addressed within the scope of this study. Suggestions for Turkey are also included. Spatial analysis was conducted using the Space Syntax method in newly constructed smart cities. Recommendations were made for the sustainability of these settlements. The findings indicate that the spatial configuration of smart city infrastructure influences the sustainability of these cities. The findings also demonstrate the significant role of local factors in the sustainability of newly constructed smart cities. This study relates sustainability and innovative practices to urban efficiency. The smart city infrastructure and newly constructed settlements are approached using a different method compared with previous studies. A review of the literature did not uncover any studies in this direction or using this method. Therefore, this study will contribute to the relevant field.

Enhancing outdoor thermal comfort in a historic site in a hot dry climate (Case study: Naghsh-e-Jahan Square, Isfahan)

Urban heat islands (UHI) pose a significant threat to the well-being of people and public health because of the more frequent and intense occurrence of heat waves in urban areas. As a result, it is crucial to prioritize enhancing thermal comfort in outdoor spaces and minimizing the impact of extreme heat in urban areas. This study focuses on historically significant Naghsh-e-Jahan Square, a UNESCO World Heritage site in Isfahan, Iran, located in BWK climate zone. This study employs the ENVI-met tool to analyze six design scenarios involving various configurations of green and blue infrastructure. Elements from both the historical and contemporary states of the square, including shading and non-shading trees (Pine and Platanus trees), as well as water in two forms (stream and pond), were investigated over a typical summer day to evaluate climatic parameters (Ta, Rh, Tmrt, and PET). Results reveal a robust correlation between Tmrt and PET; Furthermore, enhancing the green canopy with wind-aligned water surfaces maximizes PET improvement. The optimal case exhibits a 7.96 ℃ and 3.04 ℃ reduction in Tmrt and PET, changing thermal sensation from "very hot" to "warm." This study provides better understanding of passive strategies for improving outdoor thermal comfort in the historic Naghsh-e-Jahan Square.

Optimization of opportunistic utilization of the ATLAS high-level trigger farm for LHC Run 3

Optimization of opportunistic utilization of the ATLAS high-level trigger farm for LHC Run 3

Research on the Status and Countermeasures of After-school Extended Hours Service in Yunnan Primary Schools

Objective: Under the background of the "Double Reduction Policy", there is a mismatch between the time when primary school students leave school and the time when parents go off work, and picking up and dropping off children on time has become a problem for people's livelihoods. In order to solve the "three and a half hours" problem derived from this, and to further enhance the capacity of education services, the Ministry of Education issued a relevant document in 2017 to encourage the provision of custodial after-school services by schools. In order to solve the "3:30" problem and further enhance the capacity of education services, the Ministry of Education issued a relevant document in 2017, encouraging schools to provide custodial after-school services. With the support of this document, and adhering to the principle of "one school, one case", schools around the world have implemented after-school extended hours services. This study takes Zhaotong City, Yunnan Province, as an example, and uses questionnaire survey method and interview method to survey 262 primary school students and 18 teachers within Zhaotong City to understand the current situation of after-school extended hours service implementation. The survey found that the after-school extended hours service in Yunnan primary schools exists problems such as lack of characteristics in content, imperfect infrastructure configuration, low motivation of participating teachers and insufficiently strong school management. In response to the above problems, the survey proposes countermeasures such as relying on the existing conditions to explore curriculum resources, improving the basic configuration of after-school extended hours service, strengthening the management of after-school extended hours service in schools, and improving the systematic guarantee of after-school extended hours service. In order to provide a certain reference for the development of after-school extended hours service in Yunnan primary schools.

Cisco Packet Tracer modeling in the course of computer networks

The computer networking course is usually taught in a mixed mode, which includes a lecture and a practical lesson, and in addition to a full-time theoretical lesson, students must take practical classes to evaluate technologies and content. Nevertheless, the abstractions of the computer networking course, such as the multilevel complexity of the TCP/IP network, the connection and configuration of client and server infrastructure, as well as the differences in static and dynamic configuration of IP addresses, set students a huge task to understand and master the basic concept of computer networking technologies. Thus, the approach based on the use of computer network modeling and visualization tools when teaching the computer networks course is considered useful for teachers and students. In this study, Cisco Packet Tracer computer network simulation software was used in the Computer Networking Course (KJ2212). Students (N=55) got acquainted with the Cisco Packet Tracer program, on the basis of which they developed a global network (WAN) consisting of personal computer (PC) configuration operations, servers and switches in accordance with the Cisco standard. Subsequently, with the help of a survey, the opinions of students and their understanding of the effectiveness of Cisco packet Tracer in teaching computer networks were studied. All feedback was statistically studied using SPSS 16.0. From the analysis of descriptive results, all students agreed that Cisco Packet Tracer successfully helped them understand several key concepts of computer networks and at the same time eliminate some abstractions they encountered during the course (N=32: totally agree; N=23: I agree). Cisco Packet Tracer has established itself as a modeling and visualization tool as an effective software that supports computer networking course training.networking course training.

Performance analysis of distance-based resource allocation in UAV-Assisted vehicular ad hoc networks

Intelligent Transportation Systems (ITSs) have undergone a revolution due to the widespread use of vehicular networks, which have made it possible for cars and infrastructure to communicate effectively. The performance Analysis of a Road Side Unit (RSU) and an Unmanned Aerial Vehicle (UAV) in a realistic urban setting is modeled using a vehicular network modeling framework. According to our proposed protocol, when a new vehicle enters a vehicular network at any random position. Then the proposed protocol calculates the distance between the vehicle and RSU and between the vehicle and UAV. Based on the distance calculated, the position of the random vehicle concerning the UAV and RSU is determined. To reduce interference, those vehicles that are nearer to the UAV are assigned to UAV, and those that are nearer to RSU are assigned to RSU. For Successful transmission, the received power of the vehicle is compared with the pre-determined Signal-to-Interference plus Noise Ratio (SINR) threshold. The UAV may offer better throughput than the RSU in a vehicular network simulation due to its higher altitude, transmit power, antenna gain, frequency, and coverage range. We can control the distribution of vehicles between the two coverage regions by changing the UAV_distance_threshold while keeping the RSU_distance_threshold constant. This creates a dynamic system where increasing the UAV_distance_threshold results in a higher proportion of vehicles being served by UAVs and vice versa. Hence our proposed setup can optimize the positioning and configuration of communication infrastructure while considering the coverage and performance of RSUs and UAVs.

Multi-objective decision-making for green infrastructure planning: Impacts of rainfall characteristics and infrastructure configuration

Rapid urbanization has caused significant water-related problems in urban areas, including flooding and pollution. Green infrastructure has emerged as an effective solution within the realm of nature-based approaches to address these problems. However, there is a need for multi-objective decision-making in green infrastructure planning to strike a balance among various benefits, including those related to the anthroposphere and hydrosphere. Unfortunately, the impacts of rainfall characteristics and infrastructure configuration on multi-objective optimization outcomes are not well understood. To bridge this knowledge gap, a multi-objective optimization tool was developed in this study considering area, location, and hydrological linkages across green infrastructures. This tool combines the Storm Water Management Model (SWMM) and the Strength Pareto Evolutionary Algorithm 2. The proposed tool was implemented in a district-scale research region characterized by seven different rainfall patterns and four return periods. The results show that the proposed tool, integrated with the calibrated and validated SWMM, can provide rational configuration solutions for the target region. Rainfall characteristics significantly affect the cost-efficiency curve and layout of the green infrastructure, given their diverse nature. Solutions optimized by this approach yield optimal economic and environmental benefits. Notably, solutions incorporating hydrological linkages exhibit reduction rates approximately twice as high as those without such linkages. These findings may provide a workable theoretical basis for nature-based solutions and valuable guidance for urban water management.

Integrating the Spatial Configurations of Green and Gray Infrastructure in Urban Stormwater Networks

AbstractGreen infrastructure (GI) practices improve stormwater quality and reduce urban flooding, but as urban hydrology is highly controlled by its associated gray infrastructure (e.g., stormwater pipe network), GI's watershed‐scale performance depends on its siting within its associated watershed. Although many stormwater practitioners have begun considering GI's spatial configuration within a larger watershed, few approaches allow for flexible scenario exploration, which can untangle GI's interaction with gray infrastructure network and assess its effects on watershed hydrology. To address the gap in integrated gray‐green infrastructure planning, we used an exploratory model to examine gray‐green infrastructure performance using synthetic stormwater networks with varying degrees of flow path meandering, informed by analysis on stormwater networks from the Minneapolis‐St. Paul Metropolitan Area, MN, USA. Superimposed with different coverage and placements of GI (e.g., bioretention cells), these gray‐green stormwater networks are then subjected to different rainfall intensities within Environmental Protection Agency's Storm Water Management Model to simulate their hydrological benefits (e.g., peak flow reduction, flood reduction). Although only limited choices of green and gray infrastructure were explored, the results show that the gray infrastructure's spatial configuration can introduce tradeoffs between increased peak flow and increased flooding, and further interacts with GI coverage and placement to reduce peak flow and flooding at low rainfall intensity. However, as rainfall intensifies, GI ceases to reduce peak flow. For integrated gray‐green infrastructure planning, our results suggest that physical constraints of the stormwater networks and the range of rainfall intensities must be considered when implementing GI.

A Bibliometric Analysis of the Intellectual Landscape of Mobile Technology and Higher Education Research

Technology has become a crucial part of higher education. Higher education institutions have adapted to embrace technology-enabled classroom practices to meet the rising expectations of a varied student population while continually enhancing their learning experience. Mobile technology in higher education, in particular, has the opportunity to provide access to or improve education at a low cost with a less demanding infrastructure configuration. In the current study, the researchers aimed to better understand the intellectual landscape of mobile technology and higher education through bibliometric analysis of research articles published in the Scopus database. This research included a study of 277 papers published in Scopus-indexed peer-reviewed journals between 2006 and 2023. The citation network, co-citation analysis, and publication patterns were examined to discover influential work in this domain. Bibliometric analysis was used to identify the most notable journals, authors, nations, articles, and topics, followed by thoroughly examining the content of 277 papers in the identified clusters. The four major themes enumerated are—Rise of mobile learning, E-learning—the blended and collaborative way, Mobile Technologies in higher education, and Student Engagement in the times of mobile learning. The paper provides interesting insights into these emerging themes, the study will assist regulators, policymakers, and academic scholars in understanding the fundamentals of mobile technology and higher education and identifying pertinent topics for further research.

What Constitutes the Deployment and Runtime Configuration System? An Empirical Study on OpenStack Projects

Modern software systems are designed to be deployed in different configured environments (e.g., permissions, virtual resources, network connections) and adapted at runtime to different situations (e.g., memory limits, enabling/disabling features, database credentials). Such a configuration during the deployment and runtime of a software system is implemented via a set of configuration files, which together constitute what we refer to as a “configuration system.” Recent research efforts investigated the evolution and maintenance of configuration files. However, they merely focused on a limited part of the configuration system (e.g., specific infrastructure configuration files or Dockerfiles), and their results do not generalize to the whole configuration system. To cope with such a limitation, we aim to better capture and understand what files constitute a configuration system. To do so, we leverage an open card sort technique to qualitatively study 1,756 configuration files from OpenStack, a large and widely studied open source software ecosystem. Our investigation reveals the existence of nine types of configuration files, which cover the creation of the infrastructure on top of which OpenStack will be deployed, along with other types of configuration files used to customize OpenStack after its deployment. These configuration files are interconnected while being used at different deployment stages. For instance, we observe specific configuration files used during the deployment stage to create other configuration files that are used in the runtime stage. We also observe that identifying and classifying these types of files is not straightforward, as five out of the nine types can be written in similar programming languages (e.g., Python and Bash) as regular source code files. We also found that the same file extensions (e.g., Yaml ) can be used for different configuration types, making it difficult to identify and classify configuration files. Thus, we first leverage a machine learning model to identify configuration from non-configuration files, which achieved a median area under the curve (AUC) of 0.91, a median Brier score of 0.12, a median precision of 0.86, and a median recall of 0.83. Thereafter, we leverage a multi-class classification model to classify configuration files based on the nine configuration types. Our multi-class classification model achieved a median weighted AUC of 0.92, a median Brier score of 0.04, a median weighted precision of 0.84, and a median weighted recall of 0.82. Our analysis also shows that with only 100 labeled configuration and non-configuration files, our model reached a median AUC higher than 0.69. Furthermore, our configuration model requires a minimum of 100 configuration files to reach a median weighted AUC higher than 0.75.

„We are making it on ourselves“ – Infrastrukturen der (Im)Mobilität in Bosnien und Herzegowina

Abstract. Due to tightened controls at the Croatian border and pushbacks by border guards, ‚people on the move‘ are forced to stay in Bosnia and Herzegovina for a longer time. This article explores the infrastructures that refugees and other migrants use and maintain in canton Una-Sana and how they shape their movements and everyday lives. These ‚infrastructures of (im)mobility‘ fulfil a dual function: they structure mobility locally, along the Balkan route and across the EU's external border and enable life in (forced) immobility in the border space. To better understand these infrastructures, their physical, social and digital dimensions, and their patterns of (re)production need to be scrutinized. Building on central arguments of the mobility paradigm and critical migration studies, we argue that the (re)production and (re)configuration of infrastructures of (im)mobility is largely driven by highly unequal global mobility regimes and restrictive bordering practices, but that they can also become sites of autonomy and resistance against social marginalization, spatial exclusion and enforced immobilization.

Research on the optimization model for building an efficient IT infrastructure using the AWS platform

The analysis of IT infrastructure processes has shown that their manual execution without automation can be time-consuming and labor-intensive, as well as increases the risk of errors. Designing an IT infrastructure using Amazon Web Services (AWS) allows to identify the required resources and components for building an efficient infrastructure. Therefore, this study aims to improve the processes of building and managing IT infrastructure by automating them using the AWS platform. Hence, in this paper we propose a mathematical model to determine the IT infrastructure desired configuration. The proposed model assumes solving a linear programming problem with integer constraints on the optimization variables. The Branch-and-Bound algorithm is used to study the proposed mathematical model, by considering different AWS server input data and defining optimal IT infrastructure configurations.

Transformation urbaner Infrastrukturen

The transformation of urban infrastructures, such as water, energy and transport, is central for the sustainable development of cities. Those responsible for the provision of public services are increasingly under pressure to transform infrastructures to make them more sustainable. Our paper explores governance-related challenges and solutions to transforming urban infrastructures in the context of the city state of Berlin. In the form of case studies, we investigate three transdisciplinary research projects that attempt to support transformation processes in the water, energy and transport sectors respectively. The analysis draws on reports and publications, discussion with central actors from the projects as well as the city administration between 2017 and 2022. Despite differences between the projects as well as the infrastructure systems addressed, we identify some common barriers for the transformation of urban infrastructures in the city state of Berlin. Results show that local neighbourhoods are important socio-spatial units for catalysing transformation processes. They allow for experiments with more sustainable infrastructure configurations and novel governance approaches. However, these niche experiments do not scale to the mainstream, yet. Across the three infrastructure systems, we discuss potential solutions and conclude with reflections on the implications for the sustainable transformation of urban infrastructures in Berlin and beyond. English title: Transformation of urban infrastructures. Barriers and solutions from three transdisciplinary research projects on networked infrastructures in Berlin