Factors Affecting Construction Sector Safety Performance: Exploratory Factor Analysis Evidence from China

Construction industry is a significant contributor to the Chinese economy. The industry has more than 12 million employers with over 250 million employees and creates almost $1.9 trillion worth of structures yearly. Civil construction remains the main driver of growth in China. Basically, a task is developed to meet market demands or demands in a timely fashion. Different possibilities may be thought about in the conceptual drawing board, and also the technical and also financial feasibility of each alternative will be assessed and compared in order to select the very best feasible job. The construction industry in China is forecast to grow by 7.7% in 2021, driven by strong Y-o-Y growth in the first quarter, reflecting the comparison to the previous year's period when construction work was halted across most of the country. Thereafter, the construction industry is expected to record an average annual growth of 4.2% between 2022 and 2025. The industry's growth over the forecast period is expected to be driven by investments on new infrastructure, including investment in the areas of 5G networks, Artificial Intelligence, the Internet of Things, and data centers. According to the government-backed think tank, the China Electronic Information Industry Development, the country is expected to spend CNY10 trillion (US$1.4 trillion) on new infrastructure projects between 2020 and 2025. This study evaluated factors affecting construction sector performance: explanatory factor analysis evidence from China. From the literature reviewed, it was established that entering the Chinese construction market is still seen as exciting but difficult by many foreign contractors and consultants. The study found out that rising material and labor costs, labor woes, increased competition and shrinking profit margins were some of the challenges construction firms in Chin face. The study concludes that the implementation of construction safety laws and the rate of subcontracting are relevant factors affecting construction sector in China, while neither the extent of using temporary workers, nor the availability of resources, nor the level of per capita GDP has any effects. Keywords. Construction sector, safety performance, construction sector, labor costs, increased competition, shrinking profit margins

Simulation Experiment and Analysis of GNSS/INS/LEO/5G Integrated Navigation Based on Federated Filtering Algorithm

This article examines the positioning effect of integrated navigation after adding an LEO constellation signal source and a 5G ranging signal source in the context of China’s new infrastructure construction. The tightly coupled Kalman federal filters are used as the algorithm framework. Each signal source required for integrated navigation is simulated in this article. At the same time, by limiting the range of the azimuth angle and visible height angle, different experimental scenes are simulated to verify the contribution of the new signal source to the traditional satellite navigation, and the positioning results are analyzed. Finally, the article compares the distribution of different federal filtering information factors and reveals the method of assigning information factors when combining navigation with sensors with different precision. The experimental results show that the addition of LEO constellation and 5G ranging signals improves the positioning accuracy of the original INS/GNSS by an order of magnitude and ensures a high degree of positioning continuity. Moreover, the experiment shows that the federated filtering algorithm can adapt to the combined navigation mode in different scenarios by combining different precision sensors for navigation positioning.

Cloud computing security requirements: A Review

Cloud computing is a new technology that is undergoing tremendous development today. People who use it are not able to separate the reasonable from the unreasonable arguments that come with the security requirements in the cloud. The claim that cloud computing is hereditarily insecure is as absurd as the claim that cloud computing does not create new security problems. Cloud computing is a way to dynamically increase resources without the need for in-depth knowledge of a brand new infrastructure, without training new workers or designing new software solutions. The article aims to analyse the different cloud security issues and models of cloud architectures. Some of the main problems with security in virtualization, concerns about storing data in the cloud and the assessment of risk tolerance in cloud computing are presented. Legal and regulatory issues for the protection of personal data are addressed.

Smooth integration of transport infrastructure into urban space

Municipal authorities in industrialized and in developing countries face unceasingly the issues of congestion, insufficiency of transport means capacity, poor operability of transport systems and a growing demand for reliable and effective urban transport. While the expansion of infrastructure is generally considered as an undesirable option, in specific cases, when short links or ring roads are missing, new infrastructure projects may provide beneficial solutions. The upgrading and renewal of existing networks is always a challenge to the development of a modern city and the welfare of citizens. Central governance and management of transport systems, the establishment of smart and digital infrastructure, advanced surveillance and traffic monitoring, and intra-city energy-harvesting policy are some of the steps to be taken during the transition to a green and sustainable urban future.Municipal authorities have also to consider other options and strategies to create a citizen-friendly setting for mobility: diminish the need for trips (digitalization of services, e-commerce, etc.), shift from private to public transport and transform the urban form to promote non-motorized transport in favor of the natural environment and public health. A citizen-friendly policy based on the anticipation of future needs and technological development seems to be a requisite for European cities searching for a smooth integration of their networks into urban space.

Beyond the Binary: What does it take to tread the ‘Third Way’ of Urban 12 Regeneration in India?

Urbanisation is an inevitable part of India’s growth, which places enormous strain on existing infrastructure and settlements. Although the need for urban renewal or urban regeneration (as contrasted with greenfield development) is clear, it seems current policy and institutional frameworks have yet to offer any significant results. Lack of financial resources is one of the most critical challenges being faced by governments at various levels, and despite sufficient financial means and instruments to develop new infrastructure (such as the FDI, PPP, TDR, and so on), funding channels for urban renewal projects remain almost non-existent within an environment of mutual distrust. Through a discussion of three ongoing projects, the need to explore outside of conventional models will be demonstrated. In essence, this article advocates for an intermediary working structure of PPPP (Public-Private Partnership with the fourth P standing for People), which can be situated between a strict / formal approach and an unregulated / informal one, often referred to in the Indian context to as Jugaad. Though jugaad is typically characterized by ‘ad-hoc-ism’ and informality, the outcomes still provide affordable solutions for stakeholders. Jugaad is notable for both its process-driven approach involving people-to-people collaboration, and its circumvention of the need for reform of the prevailing systemic environment. We suggest, therefore, that Jugaad in urbanism be reconceived as going beyond quick-fixes to serve as a possible model for resolving challenges in a participatory manner, without resorting to rule-bound contracting methods. *Jugaad is a term applied to a creative or innovative idea providing a quick, alternative way of solving or fixing a problem.

Evaluation of Transportation Infrastructure: A Case Study of Gold Coast Light Rail Stage 1&2

Since the COVID-19 pandemic began, there has been increased reliance on new infrastructure projects to counter economic fallout and underpin employment security. Urban and inter-urban transportation projects, such as major road, rail and port facilities, are popular choices for national and state governments in Australia as they provide broad fiscal support across all sectors of the economy. The problem with stimulus is making sure that the quality of the new infrastructure provides collective utility to a community or region. Whether the benefits will be worthwhile and represent best use of resource inputs requires financial, social, ethical and environmental consequences to be evaluated in a comparable format. The aim in this paper is to analyse the Gold Coast Light Rail (GCLR) Stage 1&2 project using a method that is capable of merging tangible and intangible criteria using an ordinal ranking algorithm. While the GCLR case study is undertaken with the benefit of hindsight, normally these types of evaluations are performed in real time as a project progresses from initiation (design) to implementation (deliver) and influence (delight). The method adopted in this study represents a modern form of multi-criteria decision-making, which enables successful projects to be distinguished from unsuccessful ones using a time period from commencement until one full year of operation has occurred. The i3d3 model, developed by a team from Bond University, has the unique benefit of ranking projects from best to worst across an organisational portfolio, geographic region or industry sector. It also supports past project performance to inform new design through application of a continuous improvement process of recording lessons learned. The GCLR case study calculated 100% of the critical success factors in the model to be positive and produced an overall success ranking of 23 (on a scale of -100 to +100). This paper presents the approach taken to evaluate GCLR’s level of success and the calculations that took place to reach this finding. This is the first time i3d3 has been used on an Australian project.

La cobertura de los índices de citas abiertos se acerca a la de Web of Science y Scopus

The information sources that are often used to monitor and to obtain a better understanding of the system of scholarly communication (such as Web of Science, Scopus, and Google Scholar) have historically been distributed under restrictive use licenses. However, in a scenario where science and scientific communication are undergoing a process of digital transformation, these models do not facilitate the development of new infrastructure that is better adapted to current and future needs. At the same time, these models hamper reproducibility. In recent years, a variety of open data sources, such as Microsoft Academic, Crossref, and others, have become available, providing easy access to large collections of metadata that were previously only available from closed sources. Citation data are one type of metadata provided by these open data sources. This study documents the significant growth in coverage of open citation data that has taken place between 2019 and 2021, and the events that have led to this point. These collections of open scholarly metadata have kick-started the development of a new ecosystem of scholarly information services. However, their fragility still poses a risk for downstream applications. Academic libraries could become important allies of open scholarly metadata initiatives. Resumen Históricamente, las fuentes de información utilizadas para observar y comprender el funcionamiento del sistema de comunicación científica han sido distribuidas bajo licencias de uso restrictivas (Web of Science, Scopus, Google Scholar). En el contexto actual, caracterizado por un proceso de transformación digital de la ciencia y de la comunicación científica, estos modelos no facilitan el desarrollo de infraestructuras y herramientas de información científica adaptadas a nuevas necesidades, e impiden la realización de análisis reproducibles. Afortunadamente, en los últimos años han aparecido diversas colecciones de metadatos de investigación distribuidas bajo licencias abiertas, como las ofrecidas por Microsoft Academic, Crossref y otros. Un tipo de metadato ofrecido por estas fuentes abiertas que anteriormente solo estaba disponible desde fuentes cerradas son las relaciones de citación entre documentos académicos. Este trabajo muestra el significativo crecimiento que se ha producido entre 2019 y 2021 en la cobertura de citas disponible en fuentes abiertas, así como los pasos que han sido necesarios para llegar hasta este punto. Estas colecciones de metadatos abiertas han estimulado el desarrollo de un nuevo ecosistema de herramientas de información científica, pero su fragilidad representa un riesgo de cara al futuro. Las bibliotecas académicas podrían convertirse en importantes aliadas de estas iniciativas.

ARTIFICIAL NEURAL NETWORK FOR LONG TERM LOAD FORECASTING IN UTTARAKHAND STATE: A CASE STUDY

Electricity is one of the essential part of our life. With the increase in consumption of resources the demand of electricity is also increased. Uttarakhand as hilly state is approaching towards implementation of new Technologies and Techniques in the area of growth and suistainable development. Due to the implementation of better road infrastructure, tourism connectivity and IoT devices in various projects and inclusion of electric vehicles and their charging infrastructure in Uttarakhand State the demand of electricity has also increased. The Uttarakhand State has planned the establishment of new infrastructure by providing relaxation on various taxes and option of subsidy to investors. The exemption on xed electricity charges is provided to investors in Uttarakhand. The highest part of Electricity Generation is based on Hydro Power in Uttarakhand. By establishment of new infrastructure in Uttarakhand it would be a thrust to load generation companies to produce demanded of electricity on time. In this study the long-term load forecasting from 2022 to 2030 is analysed using Articial Neural Network. The input data is received from Uttarakhand Electricity Regulatory Commission and Uttarakhand Power Corporation Limited. The prediction is based on last 10 years data of historical load, GDP, Population, and past two years data of electric vehicles, and charging infrastructure. In this study, it has reported that by 2030 there would be huge change in infrastructure and most of diesel and petrol vehicles would come on electric vehicles. This study is focused on the Long-Term Load Forecasting in Uttarakhand State where electric vehicles and charging infrastructure load requirement is also calculated. Using Deep Learning Technique in this paper Articial Neural Network is used for forecasting the results. This tool is used to identify the consumption pattern of electricity in Uttarakhand State for further nine years from 2022 to 2030. The Government of Uttarakhand has planned Vision 2030 for the sustainable development in Uttarakhand.