Environmental Infrastructure Research Articles

Optimized load balancing mechanism in parallel computing for workflow in cloud computing environment

Cloud computing gives on-demand access to computing resources in metered and powerfully adapted way; it empowers the client to get access to fast and flexible resources through virtualization and widely adaptable for various applications. Further, to provide assurance of productive computation, scheduling of task is very much important in cloud infrastructure environment. Moreover, the main aim of task execution phenomena is to reduce the execution time and reserve infrastructure; further, considering huge application, workflow scheduling has drawn fine attention in business as well as scientific area. Hence, in this research work, we design and develop an optimized load balancing in parallel computation aka optimal load balancing in parallel computing (OLBP) mechanism to distribute the load; at first different parameter in workload is computed and then loads are distributed. Further OLBP mechanism considers makespan time and energy as constraint and further task offloading is done considering the server speed. This phenomenon provides the balancing of workflow; further OLBP mechanism is evaluated using cyber shake workflow dataset and outperforms the existing workflow mechanism.

Effects of a Gravel Pit Lake on Groundwater Hydrodynamic

In Europe, 1132 Mt of sand and gravel were mined in 2019, which causes major changes to the hydrogeological cycle. Such changes may lead to significantly raised or lowered groundwater levels. Therefore, the aggregate sector has to ensure that impacts on existing environmental and water infrastructures are kept to a minimum in the post-mining phase. Such risk assessments are often made by empirical methods, which are based on assumptions that do not meet real aquifer conditions. To investigate this effect, predictions by empirical and numerical methods about hydraulic head changes caused by a pit lake were compared. Wrobel’s equation, which is based on Sichardt’s equation, was used as the empirical method, while a numerical groundwater flow model has been solved by means of the finite-element method in FEFLOW. The empirical method provides significantly smaller ranges of increased/decreased groundwater levels caused by the gravel pit lake as the numerical method. The underestimation of the empirical results was related to the finding that field measurements during pumping tests show a larger extent of groundwater drawdown than calculations with the Sichardt’s equation. Simplifications of the 2D model approach have been evaluated against hydraulic head changes derived from a 3D groundwater model. Our results clearly show that the faster and cheaper empirical method—Wrobel’s equation, which is often preferred over the more expensive and time-consuming numerical method, underestimates the drawdown area. This is especially critical when the assignment of mining permits is based on such computations. Therefore, we recommend using numerical models in the pre-mining phase to accurately compute the extent of a gravel/sand excavation’s impacts on hydraulic head and hence more effective protection of groundwater and other related environmental systems.

Disaster Resilience Model for Establishing the Sustainable Society in the Era of Climate Crisis

The purpose of this study is to suggest a community disaster resilience model to become a sustainable society in the era of climate crisis. The climate crisis not only has a direct impact on human life, but also has a wide and severe impact on various environments surrounding humans. In fact, all spheres that make up or surround a community are affected. For example, all areas such as politics, economy, society, culture, nature, science and technology, medical health, military, and safety of a country or region are being forced to change by the climate crisis. If we refuse to change due to the climate crisis or do not accept a new paradigm, the very survival of human society will be threatened. In order to secure community disaster resilience, it is necessary to improve resilience at individual, community, and environmental levels. Efforts should be made to improve good health (psychological & physical health), quality familyship, and financial stability at the individual level. At the community level, economic growth, social capital, and cultural inclusion, and at the environmental level, infrastructure recovery, government function, and nature restoration.

데이터와 서비스 대범람의 시대, DR 데이터센터 원거리 배치를 위한 기술 및 정책 방안

Recently, in late 2022, Disaster Recovery Data Center is recognized as important due to the disruption issue of Kakao, the Korea' s #1 SNS service provider caused by a fire at their separated operating data center. In this response; the needs of establishing the Disaster Reovery Data Center, this paper is examining the brief current status of domestic and foreign data centers and D.R. data centers and analyzing the related problems. Moreover, according to three requirements (environment, communication and power infrastructure) and two criteria (site level, socio-economic/manpower/government) to find the r ight location for the data center, Jeju's strengths and weaknesses were examined, and considered with the technical and policy measures for Jeju Island to encourage for the attraction of private sector's data centers/DR data centers.

Smart destination competitiveness: underscoring its impact on economic growth

PurposeThe current study is designed to investigate the factors that foster the framing of destination competitiveness and establish the factors that drive the contribution of tourism innovations to economic growth in smart tourism destinations.Design/methodology/approachA four-year panel data were extracted from the World Economic Forum's travel and tourism competitiveness index and data were analysed using Poisson Pseudo Maximum Likelihood regression model.FindingsThe findings demonstrate that both the enabling environment and airport infrastructure significantly affect tourism's impact on the economy of the selected smart European tourism destinations. Conversely, human resources and general infrastructure display a negative correlation with tourism's contribution to the economy. However, no data in the sample support the idea that tourism policies, government prioritization or readiness of tourism information and communication technologies impact tourism's contribution to the economy. Additionally, the marginal effects indicate that improving the enabling environment and airport infrastructure can generate additional benefits for the economy through tourism.Originality/valueThe uniqueness of this study is the integration of smart tourism destinations with the measure of destination competitiveness to provide an empirical bridge that links tourism competitiveness to economic growth.

Evaluation and optimization of business environment based on sustainable development perspective: Exploring the role of the reform of government functions

AbstractThe existing research on the business environment index system has a single viewpoint, which can hardly reflect the requirements of SDGs on the business environment. Few studies have focused on the “front end” factors determining the business environment. Based on panel data from 2011 to 2020, this study measures the business environment in 275 Chinese cities and uses the ArcGIS software and Natural Breaks (Jenks) to examine its spatiotemporal characteristics. The PSM‐DID model is utilized to examine the policy implications of the reform of government functions on the business environment. The findings demonstrate that China's urban business environment's total score has risen, and its geographic characteristics are “strong in the east and weak in the west.” Among the various sub‐dimensions of the business environment, the largest contribution is the infrastructure environment, followed by the rule of law environment. The reform of government functions can improve the business environment from the second year onward. Regional and city‐level heterogeneities exist in the effects of the reform of government functions on the business environment. In addition, informatization level, population density, and consumption level can optimize the business environment. This study provides a guide for accelerating the creation of a marketized, legalized, international, and sustainable business environment.

“Commercial and political needs demand the establishment of a Black Sea port”: Infrastructure development, opportunities and anxieties in an Eastern European periphery (1860s–1870s)

This paper is the biography of a failed infrastructural project: that of building a Romanian seaport and of linking it to the mainland via a canal and/or a railway. It details its rich life, its initiators and partisans, but also its (mostly foreign) contenders; “born” in the early 1860s in a certain geopolitical, economic or infrastructural environment, the initiative morphed in the coming years in close connection and in direct competition with complementary or rival projects. While the plan of having an “independent” Romanian Black Sea port remained central to the Jibrieni project, most of its other infrastructural components were continuously reimagined, so as to fit into the Romanian government's priorities and – with them – into the extremely dynamic transportation map of Central and Eastern Europe in the 1860s–1870s.

NewsPanda: Media Monitoring for Timely Conservation Action

Non-governmental organizations for environmental conservation have a significant interest in monitoring conservation-related media and getting timely updates about infrastructure construction projects as they may cause massive impact to key conservation areas. Such monitoring, however, is difficult and time-consuming. We introduce NewsPanda, a toolkit which automatically detects and analyzes online articles related to environmental conservation and infrastructure construction. We fine-tune a BERT-based model using active learning methods and noise correction algorithms to identify articles that are relevant to conservation and infrastructure construction. For the identified articles, we perform further analysis, extracting keywords and finding potentially related sources. NewsPanda has been successfully deployed by the World Wide Fund for Nature teams in the UK, India, and Nepal since February 2022. It currently monitors over 80,000 websites and 1,074 conservation sites across India and Nepal, saving more than 30 hours of human efforts weekly. We have now scaled it up to cover 60,000 conservation sites globally.

MENGEDUKASI MASYARAKAT UNTUK MEMANFAATKAN WISATA AIK MENCERIT SEBAGAI SALAH SATU TEMPAT WISATA DI DESA PRINGGASELA DAN PEMANFAATAN MEDIA ONLINE SEBAGAI SARANA PEMASARAN PRODUK TENUN (DIGITAL MARKETING)

Pringgasela Village is a village in the Pringgasela District, East Lombok Regency, West Nusa Tenggara Province, Indonesia. Pringgasela village is surrounded by a large area of rice fields, so that most of the people there work as farmers and farm labourers, and some people make weaving crafts as an additional livelihood. Pringgasela Village itself has promising tourism potential, namely having various tourist areas (Mencrit River, Semporonan Waterfall, Goa Kopong Waterfall, Mayung Polak Waterfall, Aik Seleong Tourism Park, etc.) There is also woven fabric cultural tourism which is the main attraction the main village of Pringgasela. The condition of the area is still beautiful and natural so it has superior natural resources such as abundant water sources, fertile soil. Apart from the natural and land potential that Pringgasela Village has, there are several main problems in the village including the lack of tourists visiting, lack of public awareness of environmental cleanliness, facilities and infrastructure supporting tourism which are still inadequate. Therefore, with the 2022 Mataram University thematic KKN activities in Pringgasela Village, it is hoped that it can develop and exist the Pringgasela Village through work programs during KKN activities such as optimizing tourist and business spots, sustainable halls as a form of effort to provide understanding in handling school dropouts for children and Increasing interest in reading for elementary-junior high school age children, so that they get used to reading.

BeachLog: A multiple uses and interactive beach picture

There are some tools in place that classifies and/or rank beaches according to a series of parameters. It is possible to identify a gap in the development of tools that map and describe beaches without putting the results into a classification status of good or bad. Since beaches are important from different points of views such as ecology, tourism, economy, pollution or invasive species studies and management, fisheries, estate development, protected areas, among others it is relevant to describe and understand parameters in detail. This work offers a multi-purpose and interactive beach descriptor called BeachLog. It can be used by beachgoers to keep their own records in the same way a diver uses a Diver's LogBook, managers can use the tool to support coastal management projects, long-term monitoring, and beach description baseline. Also, BeachLog can be a didactic tool to aiming to bring environmental sciences closer to technology through the use of spreadsheets and dashboards. BeachLog is based on the more frequent parameters in the literature, selected, organized, accounted for, and altered/added according to expert opinion. We created a list of 28 parameters, all of which were described in details of what is expected to be observed by the user. They were divided into 5 groups (Environmental characteristics, Services & Infrastructure, Information & Security, Planning & Management, and Descriptive). Here, we describe 14 Brazilian beaches using the BeachLog by inputting the results as parameters presence or absence (0/1) and descriptives in a table that can be transformed into an interactive dashboard for better/easier visualization. Planning & Management was absent on all 14 beaches studied, pointing out the relevance and gaps in this group. In the other groups it was possible to observe variation in the parameter occurrence, indicating that each beach is different and it is important to observe parameters individually. Beach Litter and Invasive Species parameters from the Environmental characteristics group were present in all beaches. BeachLog showed as an easy way to describe a beach and can be a tool to support diagnosis and understanding of the beach's status.

A Case of Project Risk Management Course: Students’ Feedback on Teaching and Learning

To equip students to be capable professionals and active citizens is the goal of university teaching and learning. Effective teaching and learning are influenced by a variety of factors, including the role of lecturers in creating and delivering high-quality courses, the relevance and organization of course materials, and the learning environment. Therefore, it is crucial to get student feedback on these concerns to ensure excellent teaching and learning. Students' opinions on the course material, the lecturers' professionalism, their teaching and learning activities, and the learning environment (infrastructure) will be gathered for this study. The study also aims to look at the relationships between these components. This study's input was acquired through a survey design and a questionnaire. 132 students from project risk management classes at a public institution are participating in this study. Using IBM SPSS version 28, descriptive and correlation analysis of the feedback was performed. The results demonstrate that students' general opinions of the project risk management course's content were favorable and of high caliber. Additionally pleasant and exceptional are the lecturers' professionalism and the way they teach and study. The infrastructure is then suitable and conducive. Overall, there is a clear connection between the infrastructure, teaching and learning, professionalism of the lecturer, and the caliber of the course content. The results of this study can assist teachers in honing their teaching techniques and enhancing the caliber of their instruction.

Control of surface deformation and overburden movement in coal mine area by an innovative roadway cemented paste backfilling method using mining waste

Caving mining method could lead to massive waste rocks hauled to surface while leaving a large void in underground. This would eventually result in the surface subsidence and damage to the environment and surface infrastructures. In this study, we proposed three different backfilling methodologies to minimise the surface subsidence being 1) 100 % mining and 100 % backfilling (method 1); 2) leaving one slice of coal between two backfilled slices (method 2) and 3) leaving one slice of coal between one backfilled slice (method 3). The backfilling materials are made of waste rock, fly ash and cement and the optimal ratio has been found through the test program designed based on the orthogonal experiment design method. The strength of the backfilling paste is 3.22 MPa at the axial strain 0.033. The mine scale numerical simulation has also been conducted and it was concluded that the method 1 would lead to 0.098 m roof deformation in underground roadway whereas the method 2 and method 3 only induced a roof deformation around 32.7 % and 17.3 % of that induced by the method 1, respectively. All three methodologies have been approved to minimise the roof deformation and disturbance to the rock by mining operations. At last, the surface subsidence has been scientifically evaluated based on the probability integration method of surface movement. It indicated that the surface subsidence, horizontal movement, inclined movement and curvature of rock surrounding the panel void were all below the minimum value required by regulation. This confirmed that the selected backfilling mining is able to ensure the integrity of the surface infrastructures. This technology provides a new way to control the surface subsidence caused by coal mining.

Knowledge sharing and discovery across heterogeneous research infrastructures.

Research infrastructures play an increasingly essential role in scientific research. They provide rich data sources for scientists, such as services and software packages, via catalog and virtual research environments. However, such research infrastructures are typically domain-specific and often not connected. Accordingly, researchers and practitioners face fundamental challenges introduced by fragmented knowledge from heterogeneous, autonomous sources with complicated and uncertain relations in particular research domains. Additionally, the exponential growth rate of knowledge in a specific domain surpasses human experts' ability to formalize and capture tacit and explicit knowledge efficiently. Thus, a knowledge management system is required to discover knowledge effectively, automate the knowledge acquisition based on artificial intelligence approaches, integrate the captured knowledge, and deliver consistent knowledge to agents, research communities, and end-users. In this study, we present the development process of a knowledge management system for ENVironmental Research Infrastructures, which are crucial pillars for environmental scientists in their quest for understanding and interpreting the complex Earth System. Furthermore, we report the challenges we have faced and discuss the lessons learned during the development process.

Spatio-temporal patterns of Chinese urban recovery and system resilience under the pandemic new normal

Enhancing urban resilience is an important measure to improve preparedness to public health challenges; therefore, understanding the patterns and determinants of urban recovery is of great significance for sustainable urban development under the pandemic new normal. We first propose an analytical framework of urban recovery capacity, and then apply the geographical detector model and geographic weighted regression model to investigate the dynamic characteristics of urban resilience and urban recovery capacity under the impact of COVID-19 in China. The results show that the overall pattern of vitality recovery follows the U-curve; however, the impact of COVID-19 on each region is significantly different, with the highest degree of recovery in the Northwest and East, and the lowest in the Central and West. The geographical detector model reveals that urban resilience indicators can predominantly explain the variations of urban recovery across cities. The geographically weighted regression model shows that environmental resilience, infrastructure resilience, and social resilience are positively correlated with urban recovery capacity, while economic resilience cannot improve urban recovery capacity in the short term. We suggest promoting urban system diversity and redundancy across different dimensions to enhance urban resilience, but caution that linearly promoting systemic redundancy might harm the long-term sustainability of resource allocations.

Consequences of Environmental Infrastructure Deficit on Water Security and Maternal Health

Consequences of Environmental Infrastructure Deficit on Water Security and Maternal Health

A feasibility study of LoRaWAN-based wireless underground sensor networks for underground monitoring

With the continuous expansion of human interaction with the underground space, the observation of underground environment (e.g. soil moisture) and underground infrastructure (e.g. underground pipelines), as well as the monitoring and prevention of geological disasters (e.g., landslide and urban sinkholes) has attracted increasing attention and become a research focus. However, most of the traditional observation technologies are still facing difficulties in dynamic and continuous in-situ observations/monitoring within the complex underground environment. To solve this problem, this study adopts LoRaWAN-based wireless underground sensor networks (WUSNS) to monitor the underground environment or infrastructure. Furthermore, the feasibility of LoRaWAN-based WUSNs for underground monitoring is systematically demonstrated and presented in this article. Based on our recent validation of LoRa-based underground point-to-point channel model, we evaluate its network-level performance in this paper. We firstly develop a network simulator of LoRaWAN-based WUSNs to provide the feasibility analysis and experimental guidance for underground monitoring. Using this simulator, we numerically demonstrate that the LoRaWAN-based WUSNs technology is capable of underground monitoring over a large area and at great depths. We further certify that an appropriate selection of the physical layer parameters in various underground conditions is beneficial for underground observation. Finally, the balance between data receiver rate and network energy consumption can be implemented using different physical layer parameters for various underground monitoring applications. These results successfully demonstrate the efficient protocol development of LoRaWAN-based WUSNs and their applicability for underground monitoring applications.

Development of a research environment for the operational and computational architecture of central bank digital currency software

Objectives. The development and implementation of information and computing architecture and information support for a state central bank digital currency (CBDC) is based on the selection of a software and hardware platform, including technologies and methods for supporting interaction between the elements of the computing complex. The implementation of CBDC technologies significantly depends both on the operational and computing architecture, as well as on the technological characteristics of the means for implementing digital currency information support, which determines the need to develop an appropriate research environment. Thus, the present study sets out to develop an infrastructure for the experimental research environment of the operational and computing architecture used to provide information support for the CBDC.Methods. Digital technologies required for forming an CBDC implementation stack are under development in many countries of the world. The basis for the formation of a software and hardware complex for providing CBDC information support is comprised of theoretical and experimental studies into contemporary digital transaction management tools.Results. The main architectural and technological components that make up the CBDC operational and computing environment comprise operational and computing architectures, blockchain technologies, consensus algorithms, and various forms of digital currencies. Five CBDC operational and computing architecture options are presented. Information models of interaction between the participants in transactions of the central bank digital currency were studied with the aim of establishing the effects of an architectural solution to the characteristics of the computing complex used to provide information support. Features of various digital currencies in the form of accounts and tokens were analyzed.Conclusions. A research environment infrastructure for the CBDC operational and computing information support architecture has been developed. The prerequisites for a comprehensive analysis of the technological characteristics of the CBDC operational and computing environment are set out along with a comparison of operational and computing architecture variants. As a result of the analysis, a summary list of the characteristics of the studied architectures is drawn up. This provides for selecting the optimal operational and computing architecture depending on the requirements imposed on the CBDC.

Modern Neural Network Technologies Text-to-Image

This paper discusses state-of-the-art graphical text-to-image neural networks and methods for text-to-image conversion, analyzing the results achieved and samples created to date for text-to-image conversion tasks. Ways of applying neural network approaches to text-to-image transformation for environmental monitoring, infrastructure and medical data analysis tasks are proposed. In this paper the results of neural network generation and its correlation with the user input linguistic constructions of text queries are reviewed, and the typical flaws and artifacts typical of the neural network generated images are identified and classified. The rapid development of neural network technologies in this field could have a significant impact on society, the professional market and the media, which makes the task of studying neural network images and identifying them among other graphic content particularly relevant.

Physical activity promotion in daycare centres in Germany: study protocol for a cross-sectional survey within the BeweKi study

IntroductionIn Germany, a total of 92.2% of children between the age of 3 and school entry age attend daycare centres. Therefore, daycare centres are a suitable setting to promote physical...

What drives MLOps adoption? An analysis using the TOE framework

ABSTRACT MLOps is essential to streamline the machine learning (ML) development process, ensure ML models stay operational, and provide users with the desired value. MLOps enhances the auditability, dependability, repeatability, and quality of ML data, models, and systems. MLOps technologies tackle several operational difficulties in an ML process. This research used the TOE framework to identify drivers and challenges to adopting MLOps tool. Data were collected from 277 professionals from various industries and AI/ML-related job roles. The responses were analysed using a three-step approach – Data Profiling, Chi-square tests and Logistic regression (LR) model. The analysis uncovered that ML usage, performance drivers, and security drive MLOps adoption, whereas regulatory environment, organizational preparation, and ML infrastructure moderately influence it. The investigation shows that management/leadership needs to be aware of MLOps technologies' benefits. This study provides insights to AI/ML professionals, academics, researchers, and machine learning model users on MLOps adoption.