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Using the strong motion data of K-net in Japan, the continuous magnitude prediction method based on support vector machine (SVM) was studied.

In the range of 0.5–10.0 s after the P-wave arrival, the prediction time window was established at an interval of 0.5 s. 12 P-wave characteristic parameters were selected as the model input parameters to construct the earthquake early warning (EEW) magnitude prediction model (SVM-HRM) for high-speed railway based on SVM.

The magnitude prediction results of the SVM-HRM model were compared with the traditional magnitude prediction model and the high-speed railway EEW current norm. Results show that at the 3.0 s time window, the magnitude prediction error of the SVM-HRM model is obviously smaller than that of the traditional τ_c method and P_d method. The overestimation of small earthquakes is obviously improved, and the construction of the model is not affected by epicenter distance, so it has generalization performance. For earthquake events with the magnitude range of 3–5, the single station realization rate of the SVM-HRM model reaches 95% at 0.5 s after the arrival of P-wave, which is better than the first alarm realization rate norm required by “The Test Method of EEW and Monitoring System for High-Speed Railway.” For earthquake events with magnitudes ranging from 3 to 5, 5 to 7 and 7 to 8, the single station realization rate of the SVM-HRM model is at 0.5 s, 1.5 s and 0.5 s after the P-wave arrival, respectively, which is better than the realization rate norm of multiple stations.

At the latest, 1.5 s after the P-wave arrival, the SVM-HRM model can issue the first earthquake alarm that meets the norm of magnitude prediction realization rate, which meets the accuracy and continuity requirements of high-speed railway EEW magnitude prediction.

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.

The purpose of this paper is to reflect on what can be learned about disaster risk reduction (DRR) from the L’Aquila trial of scientists. The court case was initiated because of a controversial meeting on 31 March 2009 of the Major Risks Committee (MRC), held under the auspices of the Italian Department of Civil Protection. The purpose of the meeting was to consider (prior to the fatal earthquake of 6 April 2009) disaster risk in the L’Aquila area, which was being affected by an earthquake swarm since October 2008.

The authors undertook a document analysis of trial materials, and a review of academic and media commentary about the trial.

The legal process revealed that disaster governance was inadequate and not informed by the DRR paradigm or international guidelines. Risk assessment was carried out only in a techno-scientific manner, with little acknowledgement of the social issues influencing risks at the local community level. There was no inclusion of local knowledge or engagement of local people in transformative DRR strategies.

Most previous commentary is inadequate in terms of not considering the institutional, scientific and social responsibilities for DRR as exposed by the trial. This paper is unique in that it considers the contents of the MRC meeting as well as all trial documents. It provides a comprehensive reflection on the implications of this case for DRR and the resilience of peoples and places at risk. It highlights that a switch from civil protection to community empowerment is needed to achieve sustainable outcomes at the local level.

Giant orthogonal grid barrel vault is generated by deleting members in the inessential force transfer path of the two-layer lattice barrel vault. Consisting of members in the essential transfer path only, giant orthogonal grid barrel vault is a new type of structure with clear mechanical behavior and efficient material utilization. The paper aims to discuss this issue.

The geometrical configuration of this structure is analyzed, and the geometrical modeling method is proposed. When necessary parameters are determined, such as the structural span, length, vault rise, longitudinal and lateral giant grid number and section height to top chord length ratio of the lattice member, the structure geometrical model can be generated.

Numerical models of giant orthogonal grid barrel vaults with different rise–span ratios are built using the member model that can simulate the pre-buckling and post-buckling behavior. So the possible member buckle-straighten process and the plastic hinge form–disappear process of the structure under strong earthquake can be simulated.

Seismic analysis results indicate that when the structure damages under strong earthquake there are a large number of buckling members and few endpoint plastic hinges in the structure. Dynamic damage of giant orthogonal grid barrel vault under strong earthquake is caused by buckling members that weaken the structural bearing capacity.

This paper aims to examine the integration of lateral transshipment and road vulnerability into the humanitarian relief chain in light of affected area priority to address equitable distribution and assess the impact of various parameters on the total average inflated distance traveled per relief item.

After identifying comprehensive critical criteria and subcriteria, a hybrid multi-criteria decision-making framework was applied to obtain the demand points’ weight and ranking in a real-life earthquake scenario. Direct shipment and lateral transshipment models were then presented and compared. The developed mathematical models are formulated as mixed-integer programming models, considering facility location, inventory prepositioning, road vulnerability and quantity of lateral transshipment.

The study found that the use of prioritization criteria and subcriteria, in conjunction with lateral transshipment and road vulnerability, resulted in a more equitable distribution of relief items by reducing the total average inflated distance traveled per relief item.

To the best of the authors’ knowledge, this study is one of the first research on equity in humanitarian response through prioritization of demand points. It also bridges the gap between two areas that are typically treated separately: multi-criteria decision-making and humanitarian logistics.

This is the first scholarly work in Shiraz focused on the equitable distribution system by prioritization of demand points and assigning relief items to them after the occurrence of a medium-scale earthquake scenario considering lateral transshipment in the upper echelon.

The paper clarifies how to prioritize demand points to promote equity in humanitarian logistics when the authors have faced multiple factors (i.e. location of relief distribution centers, inventory level, distance, lateral transshipment and road vulnerability) simultaneously.

Chiang Rai being an earthquake-prone city, it is essential to raise awareness about earthquake safety and readiness, especially amongst the elderly population who spend most of their time at home. The purpose of this paper is to evaluate the earthquake preparedness of elders in relation to knowledge, attitude and practice.

This was an analytic cross-sectional study. Research data were collected from 480 elders of 60 years old and above. The research instruments were questionnaires about knowledge, attitude and self-assessment of practices in earthquake situations. Data were analyzed by number, percentage and a χ² test.

Of participants interviewed, 39.4 percent were aged between 60 and 66 years old. Overall, 94.0 percent of them had already experienced an earthquake, with 79.4 percent having experienced it in 2014. Participants had a good level of knowledge and attitude toward earthquake safety. Their practices toward earthquake readiness, however, were insufficient due to the lower practice scores (<12), especially found in the high seismic zone. The score level of knowledge, attitude and self-assessment of practice in earthquake situations showed that there is a difference in statistical significance (p<0.05).

This study focuses attention on the need to increase levels of preparedness. Safety instructions and earthquake drills should be promoted and supported in order to prepare elders for an earthquake in the study area. Research findings identified in this study will help to address the specific needs of the elderly when implementing an earthquake disaster risk reduction plan.

The purpose of this paper is to deliver a detailed analysis of the functioning of upstream–downstream interface process of the tsunami early warning and mitigation system in Sri Lanka. It also gives an understanding of the social, administrative, political and cultural complexities attached to the operation of interface mechanism, and introduces an analytical framework highlighting the significant dynamics of the interface of tsunami early warning system in Sri Lanka.

Through the initial literature review, a conceptual framework was developed, highlighting the criteria against which the interface process can be assessed. This framework was used as the basis for developing data collection tools, namely, documentary analysis, semi-structured interviews and observations that focused on the key stakeholder institutions in Sri Lanka. Thematic analysis was used to analyze the data according to the conceptual framework, and an improved and detailed framework was developed deriving from the findings.

The manner in which the interface mechanism operates in Sri Lanka’s tsunami early warning system is discussed, providing a detailed understanding of the decision-making structures; key actors; standardisation; technical and human capacities; socio-spatial dynamics; coordination among actors; communication and information dissemination; and the evaluation processes. Several gaps and shortcomings were identified with relation to some of these aspects, and the significance of addressing these gaps is highlighted in the paper.

A number of recommendations are provided to address the existing shortcomings and to improve the overall performance of tsunami warning system in Sri Lanka.

Based on the findings, a framework was developed into a more detailed analytical framework that depicts the interface operationalisation in Sri Lanka, and can also be potentially applied to similar cases across the world. The new analytical framework was validated through a focus group discussion held in Sri Lanka with the participation of experts and practitioners.

Traditional classification algorithms always have an incorrect prediction. As the misclassification rate increases, the usefulness of the learning model decreases. This paper presents the development of a wisdom framework that reduces the error rate to less than 3% without human intervention.

The proposed WisdomModel consists of four stages: build a classifier, isolate the misclassified instances, construct an automated knowledge base for the misclassified instances and rectify incorrect prediction. This approach will identify misclassified instances by comparing them against the knowledge base. If an instance is close to a rule in the knowledge base by a certain threshold, then this instance is considered misclassified.

The authors have evaluated the WisdomModel using different measures such as accuracy, recall, precision, f-measure, receiver operating characteristics (ROC) curve, area under the curve (AUC) and error rate with various data sets to prove its ability to generalize without human involvement. The results of the proposed model minimize the number of misclassified instances by at least 70% and increase the accuracy of the model minimally by 7%.

This research focuses on defining wisdom in practical applications. Despite of the development in information system, there is still no framework or algorithm that can be used to extract wisdom from data. This research will build a general wisdom framework that can be used in any domain to reach wisdom.

The 2019 Global Assessment Report on Disaster Risk Reduction (GAR) cites earthquakes as the most damaging natural hazard globally, causing billions of dollars of damage and killing thousands of people. Earthquakes have the potential to drastically impact physical, social and economic landscapes; to reduce this risk, earthquake early warning (EEW) systems have been developed. However, these technical EEW systems do not operate in a vacuum; the inequities in social systems, along with the needs of diverse populations, must be considered when developing these systems and their associated communication campaigns.

This article reviews aspects of social vulnerability as they relate to ShakeAlert, the EEW system for the USA. The authors identified two theories (relationship management theory and mute group theory) to inform self-reflective questions for agencies managing campaigns for EEW systems, which can assist in the development of more inclusive communication practices. Finally, the authors suggest this work contributes to important conversations about diversity, equity and inclusion (DEI) issues within early warning systems and earthquake preparedness campaigns in general.

To increase inclusivity, Macnamara (2012) argues that self-reflective questioning while analyzing perspective, philosophy and approaches for a campaign can help. Specific to EEW campaigns, developers may find self-reflective questions a useful approach to increase inclusion. These questions are guided by two theories and are explored in the paper.

Several research limitations exist. First, this work explores two theories to develop a combined theoretical model for self-reflective questions. Further research is required to determine if this approach and the combination of these two theories have adequately informed the development of the reflective questions.

The authors could find little peer-reviewed work examining DEI for EEW systems, and ShakeAlert in particular. While articles on early warning systems exist that explore aspects of this, EEW and ShakeAlert, with its very limited time frames for warnings, creates unique challenges.

Breast cancer is an important medical disorder, which is not a single disease but a cluster more than 200 different serious medical complications.

The new artificial bee colony (ABC) implementation has been applied to probabilistic neural network (PNN) for training and testing purpose to classify the breast cancer data set.

The new ABC algorithm along with PNN has been successfully applied to breast cancers data set for prediction purpose with minimum iteration consuming.

The new implementation of ABC along PNN can be easily applied to times series problems for accurate prediction or classification.