Search results

The purpose of this study is to introduce the top-level design ideas and the overall architecture of earthquake early-warning system for high speed railways in China, which is based on P-wave earthquake early-warning and multiple ways of rapid treatment.

The paper describes the key technologies that are involved in the development of the system, such as P-wave identification and earthquake early-warning, multi-source seismic information fusion and earthquake emergency treatment technologies. The paper also presents the test results of the system, which show that it has complete functions and its major performance indicators meet the design requirements.

The study demonstrates that the high speed railways earthquake early-warning system serves as an important technical tool for high speed railways to cope with the threat of earthquake to the operation safety. The key technical indicators of the system have excellent performance: The first report time of the P-wave is less than three seconds. From the first arrival of P-wave to the beginning of train braking, the total delay of onboard emergency treatment is 3.63 seconds under 95% probability. The average total delay for power failures triggered by substations is 3.3 seconds.

The paper provides a valuable reference for the research and development of earthquake early-warning system for high speed railways in other countries and regions. It also contributes to the earthquake prevention and disaster reduction efforts.

Indoor air quality monitoring is extremely important in urban, industrial areas. Considering the devastating effect of declining quality of air in major part of the countries like India and China, it is highly recommended to monitor the quality of air which can help people with respiratory diseases, children and elderly people to take necessary precautions and stay safe at their homes. The purpose of this study is to detect air quality and perform predictions which could be part of smart home automation with the use of newer technology.

This study proposes an Internet-of-Things (IoT)-based air quality measurement, warning and prediction system for ambient assisted living. The proposed ambient assisted living system consists of low-cost air quality sensors and ESP32 controller with new generation embedded system architecture. It can detect Indoor Air Quality parameters like CO, PM2.5, NO2, O3, NH3, temperature, pressure, humidity, etc. The low cost sensor data are calibrated using machine learning techniques for performance improvement. The system has a novel prediction model, multiheaded convolutional neural networks-gated recurrent unit which can detect next hour pollution concentration. The model uses a transfer learning (TL) approach for prediction when the system is new and less data available for prediction. Any neighboring site data can be used to transfer knowledge for early predictions for the new system. It can have a mobile-based application which can send warning notifications to users if the Indoor Air Quality parameters exceed the specified threshold values. This is all required to take necessary measures against bad air quality.

The IoT-based system has implemented the TL framework, and the results of this study showed that the system works efficiently with performance improvement of 55.42% in RMSE scores for prediction at new target system with insufficient data.

This study demonstrates the implementation of an IoT system which uses low-cost sensors and deep learning model for predicting pollution concentration. The system is tackling the issues of the low-cost sensors for better performance. The novel approach of pretrained models and TL work very well at the new system having data insufficiency issues. This study contributes significantly with the usage of low-cost sensors, open-source advanced technology and performance improvement in prediction ability at new systems. Experimental results and findings are disclosed in this study. This will help install multiple new cost-effective monitoring stations in smart city for pollution forecasting.

The purpose of this study results and recommendations will have a paramount significance for policymakers, policy advocates, development planners and practitioners who may be in need of such information for reconsideration, evaluation and inclusion into their respective development and humanitarian programming and operational strategies. Above all, the study result has further provided the local community with viable adaptation strategies to climate-induced changes in the study area.

This study was conducted to measure the livelihood vulnerability of Borana pastoralists to climate change and variability in southern Ethiopia. Pastoralists’ households were sampled using multistage sampling techniques. A total of 27 socio-economic and biophysical indicators were used to reflect vulnerability components: adaptive capacity, exposure and sensitivity. Principal component analysis was used to develop weights for indicators and to produce livelihood vulnerability index to classify households according to their level of vulnerability. Ordinal logistic regression was used to identify the determinants of vulnerability to climate-induced stresses.

The results showed that 24.4% of households were highly vulnerable, 60.3% were moderately vulnerable and 15.3% of households were less vulnerable to climate-induced stresses. Factor estimates of the logistic model further revealed that early warning information, bush encroachment, coping strategy, temperature, drought frequency, provision of humanitarian services and food shortage during the normal season of the year have a significant influence on vulnerability in the study area.

The study’s results and recommendations will be of great significance to policymakers, development planners, and practitioners who require such information for reconsideration, evaluation, and inclusion in their respective development and humanitarian program and operational strategies. Most importantly, the study’s findings have provided the local community with practical adaptation strategies to climate-induced changes in the study area.

The study explored pastoralist perception of climate change and variability and measured the livelihood vulnerability of pastoralists’ households to climate change and variability and finally investigated viable adaptation and coping strategies in the study area.

The aim of this study is to empirically explore and analyze the concrete tasks of output measurement and the inherent challenges related to these tasks in a traditional and autonomous professional public work setting – the judicial system.

The analysis of the tasks is based on a categorization of general performance measurement motives (control-motivate-learn) and main stakeholder levels (society-organization-professionals). The analysis is exploratory and conducted as an empirical content analysis on materials and reports produced in two performance improvement projects conducted in European justice organizations.

The identified main tasks in the different categories are related to managing resources, controlling performance deviations, and encouraging improvement and development of performance. Based on the results, key improvement areas connected to output measurement in professional public organizations are connected to the improvement of objectivity and fairness in budgeting and work allocation practices, improvement of output measures' versatility and informativeness to highlight motivational and learning purposes, improvement of professional self-management in setting output targets and producing outputs, as well as improvement of organizational learning from the output measurement.

The paper presents empirically founded practical examples of challenges and improvement opportunities related to the tasks of output measurement in professional public organization.

This paper fulfils an identified need to study how general performance management motives realize as concrete tasks of output measurement in justice organizations.

The purpose of this paper is to critically investigate the Ethiopia’s climate change adaptation and mitigation regulatory frameworks and their congruency with the guiding principles under the United Nations (UN) Climate Convention, to show the alignment of the regulatory frameworks with the UN Climate Change rules. Rising temperatures, erratic rainfall distribution, recurrent droughts and floods require robust climate change mitigation and adaptation policies and effective implementation in the country.

Through the doctrinal legal research method, the author has used a detailed analysis of primary sources, both national and international legislative enactments. Besides, the research has benefitted from secondary sources like research reports, online publications, scientific journals, international reports, books and journal articles.

The findings reveal that in Ethiopia, there is no national climate change-specific policy and legislation. Although there are scattered sectoral climate-related policies and strategies, they are not consistent with the principles of the United Nations Framework Convention on Climate Change (UNFCCC).

This study argues that having comprehensive specific climate change policy and legislative frameworks consistent with UNFCCC guiding principles could help to mitigate and adapt to the adverse effects of climate change in the country.

Small- and medium-sized enterprises (SMEs) often lack adequate accounting systems and may even fail because of accounting inefficiencies. Indeed, accounting can mitigate the course of a crisis and support a troubled SME’s turnaround. Its impact on reorganization success, however, has scarcely been researched so far. Therefore, this paper aims to examine the effects of several accounting parameters, namely, the quality of accounting systems, quality of early warning systems, formal planning, the standard of financial accounting and reorganization planning on the short- and long-term success of court-supervised reorganization.

The impact of accounting on reorganization success is investigated in a sample of all SME bankruptcy cases with ten or more employees (n = 117) in Upper Austria in 2012 including data for short-term survival (in 2016) and long-term survival (in 2019).

This study found evidence that the general quality of accounting systems, the quality of early warning systems and written reorganization plans positively influence the outcomes of the analyzed court-supervised reorganizations of SMEs. In particular, the existence of a reorganization plan significantly increases the short- and long-term reorganization success by ensuring the efficient and effective use of resources in the reorganization process.

This study should increase the awareness of SMEs’ owner managers, consultants, creditors and legislators for the importance of accounting in the context of reorganization. The fact that the effect of accounting on reorganization success is less pronounced in the long-term view indicates the necessity of increasing the strategic focus in SMEs’ accounting instruments.

This study provides new evidence on the impact of specific accounting parameters on the short- and long-term success of the court-supervised reorganization of SMEs. Furthermore, this study points out the high relevance of reorganization plans for SMEs.

This study aims to improve the rules and regulations system of high-speed rail emergency disposal.

Based on the analysis of the demands, rules and regulations of China concerning on-site high-speed rail emergency disposal, basic principles for revising the regulations on railway technical management (RRTM) are proposed and suggestions and evaluation methods according to the main clauses are put forward.

Basic principles for revising the RRTM are proposed, namely “to meet the actual needs of on-site high-speed railway emergency disposal, standardize the emergency disposal process, improve the efficiency of emergency disposal and keep the consistency between provisions of emergency disposal”. Existing provisions related to emergency disposal efficiency, scenarios, safety and service quality are made up for the deficiencies. To make up for the deficiencies of the existing provisions related to emergency disposal efficiency, improvement of emergency disposal scenarios and guarantee of emergency disposal safety and quality, this paper puts forward suggestions on revising 15 emergency disposal provisions of the RRTM with regard to earthquake monitoring and warning, in-station foreign body invasion warning, air conditioning failure of EMU trains and forced parking of trains in sections. A fuzzy comprehensive evaluation model based on the analytic hierarchy process (AHP) is constructed to evaluate the proposed revision scheme and suggestions, which has been highly recognized by experts.

This study implements the goal of high-quality railway development.

This study aims to compare the humanitarian supply chains and logistics of two countries in earthquake preparedness by modifying and using a previously established preparedness evaluation framework.

A European flood emergency management system (FEMS) is a seven-dimensional framework to assess a country’s preparedness for flood emergencies. The FEMS framework was modified to apply to earthquakes. Leveraging a multiple explanatory case study approach with data analysis, the authors reconstructed the events of the earthquakes in Pakistan (2005) and Japan (2011) with an applied grading (1–5). Findings were evaluated within the adopted FEMS framework. From a practitioner’s perspective, the framework is applicable and can accelerate support in the field.

Pakistan lacked emergency plans before the 2005 earthquake. In contrast, Japan possessed emergency plans before the disaster, helping minimise casualties. Overall, Japan demonstrated considerably better emergency management effectiveness. However, both countries significantly lacked the distribution of responsibilities among actors.

Practical factors in the humanitarian supply chain are well understood. However, synthesising individual factors into a comprehensive framework is difficult, which the study solves by applying and adopting the FEMS framework to earthquakes. The developed framework allows practitioners a structured baseline for prioritising measures in the field. Furthermore, this study exemplifies the usefulness of cross-hazard research within emergency management and preparedness in a real-world scenario.

This study aims to analyze the perceptions of smallholder farmers on climate change and events and further explores climate change adaptation strategies and associated challenges. The findings provide useful information for enhancing the adaptive capacity of smallholder farmers to adjust to climate-related hazards and improve their resilience and disaster preparedness in northern Ghana.

This study uses a multistage sampling procedure and sample size of 150 farmers, the Binary Probit Model (BPM), to identify and examine the determinants of climate change adaptation strategies adopted by smallholder farmers. Also, the constraints of adaptation were analyzed using Kendall’s coefficient of concordance.

The results from the BPM and statistics of Kendall’s coefficient revealed that the farm risk level, ability to adapt, farmer’s income, age, farming experience, climate change awareness and extension visits were factors that significantly influenced the adaptation strategies of smallholder farmers (in order of importance). The majority (60%) of the farmers ranked farm risk level as the major constraint to adopting climate change strategies.

The findings of this study enhance understanding on access to relevant and timely climate change adaptation information such as an early warning to farmers during the start of the farming/rainy season to support their adaptive responses to climate change.

In recent years, railway systems worldwide have faced challenges such as the modernization of engineering projects, efficient management of intelligent digital railway equipment, rapid growth in passenger and freight transport demands, customized transport services and ubiquitous transport safety. The transformation toward intelligent digital transformation in railways has emerged as an effective response to the formidable challenges confronting the railway industry, thereby becoming an inevitable global trend in railway development.

This paper, therefore, conducts a comprehensive analysis of the current state of global railway intelligent digital transformation, focusing on the characteristics and applications of intelligent digital transformation technology. It summarizes and analyzes relevant technologies and applicable scenarios in the realm of railway intelligent digital transformation, theoretically elucidating the development process of global railway intelligent digital transformation and, in practice, providing guidance and empirical examples for railway intelligence and digital transformation.

Digital and intelligent technologies follow a wave-like pattern of continuous iterative evolution, progressing from the early stages, to a period of increasing attention and popularity, then to a phase of declining interest, followed by a resurgence and ultimately reaching a mature stage.

The results offer reference and guidance to fully leverage the opportunities presented by the latest wave of the digitalization revolution, accelerate the overall upgrade of the railway industry and promote global collaborative development in railway intelligent digital transformation.