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This study investigated pre-evacuation times and evacuation behaviors of vulnerable people during the 2018 flooding in Shimobara, Okayama, Japan, and the flood-triggered factory explosion, a natural hazard-triggered technological accident known as a natural-hazard-triggered technological accidents (Natech). This study examined factors that affected evacuation decisions and pre-evacuation time, estimated the evacuation time in case of no explosion and identified community disaster prevention organization response efforts for vulnerable people.

Interviews with all 18 vulnerable people who experienced the event were conducted. Multiple regression analysis was used to examine the effect of six factors on evacuation time and reasons for delayed evacuation.

Factors affecting evacuation decisions included the sound of the explosion, followed by recommendations from relatives and the community disaster prevention organization. Explosion-related injuries delayed early evacuation, but experience of previous disasters and damage had a positive effect on early evacuation. The explosion sound accelerated evacuation of non-injured people; however, explosion-related injuries significantly delayed evacuation of injured individuals. The Shimobara community disaster prevention organization’s disaster response included a vulnerable people registry, visits to all local households and a multilayered approach that enabled monitoring of all households.

This is the first study to examine the evacuation behavior of vulnerable people and community responses during a Natech event.

The purpose of this paper is to solve the problem that the location of the initiation point cannot be measured accurately in the shallow underground space, this paper proposes a method, which is based on fusion of multidimensional vibration sensor information, to locate single shallow underground sources.

First, in this paper, using the characteristics of low multipath interference and good P-wave polarization in the near field, the adaptive covariance matrix algorithm is used to extract the polarization angle information of the P-wave and the short term averaging/long term averaging algorithm is used to extract the first break travel time information. Second, a hybrid positioning model based on travel time and polarization angle is constructed. Third, the positioning model is taken as the particle update fitness function of quantum-behaved particle swarm optimization and calculation is performed in the hybrid positioning model. Finally, the experiment verification is carried out in the field.

The experimental results show that, with root mean square error, spherical error probable and fitness value as evaluation indicators, the positioning performance of this method is better than that without speed prediction. And the positioning accuracy of this method has been improved by nearly 30%, giving all of the three tests a positioning error within 0.5 m and a fitness less than 1.

This method provides a new idea for high-precision positioning of shallow underground single source. It has a certain engineering application value in the fields of directional demolition of engineering blasting, water inrush and burst mud prediction, fuze position measurement, underground initiation point positioning of ammunition, mine blasting monitoring and so on.

This paper aims to explore how the phenomena of corruption and fraud in the public sector have been portrayed in the literature using the Audit Society Framework (Power, 1997).

The authors conducted a structured literature review (Massaro et al., 2016) to unveil relevant literature in the area of corruption and fraud in the public sector.

Results highlight that the literature using “The Audit Society” theory is still scant. Notwithstanding the call for a more decisive role of auditors in fighting corruption and fraud, much is still to be discovered about consequences of auditing and what “good quality” is.

The main limitation is that only literature in English has been included.

This paper helps practitioners and policymakers to take and implement informed decisions with regards to the fight against fraud and corruption.

In calling for more research in the domain of audit, fraud and corruption in the public sector, this paper promotes a higher focus of society on public interest and the common good.

This paper investigates one part of The Audit Society related to corruption and fraud, topics that are still very underdeveloped and unexplored by researchers. From the findings the authors suggest possible new avenues for further research.

The purpose of this commentary paper is to analyze the burst of joy experienced by global football fans when England lost the final match during the Euro 2020 against Italy.

The author worked with netnography (Internet ethnography), gathering material from the internet.

The author would consider the emotional explosion as a creative expression that was possible to happen through football. Football is not only a part of popular culture, it also creates it. It acted as a platform allowing for emotional engagement and covering different issues connected to global politics.

It is just a small study based on very limited material (Internet sources). However, it highlights every-day use of Internet and the possible amplification of certain sentiments if allowed.

Methodologically, it shows how Internet sources might be used when connected to football. It also provides an insight how Internet users can exchange opinions using sports (e.g. football) as a background.

This text highlights that football can be used as a platform do express/discuss difficult issues and that average citizens can be heard just because the platform is football.

To the author’s knowledge there is no academic text with this issue in focus yet.

This paper aims to explore how the cross-fertilization of knowledge and technologies in EU-funded research projects, including serious games and gamification, is influenced by the following variables: multidisciplinarity, knowledge base and organizations (number and diversity). The interrelation of actors and projects form a network of innovation. The largest contribution to cross-fertilization comes from the multidisciplinary nature of projects and the previous knowledge and technology of actors. The analysis draws on the understanding of how consortia perform as an innovation network, what their outcomes are and what capabilities are needed to reap value.

All the research projects including serious games and/or gamification, funded by the EU-Horizon 2020 work programme, have been analyzed to test the hypotheses in this paper. The study sample covers the period between 2014 and 2016 (June), selecting the 87 research projects that comprised 519 organizations as coordinators and participants, and 597 observations – because more organizations participate in more than one project. The data were complemented by documentary and external database analysis.

To create cross-fertilization of knowledge and technologies, the following emphasis should be placed on projects: partners concern various disciplines; partners have an extensive knowledge base for generating novel combinations and added-value technologies; there is a diverse typology of partners with unique knowledge and skills; and there is a limited number of organizations not too closely connected to provide cross-fertilization.

First, the database sample covers a period of 30 months. The authors’ attention was focused on this period because H2020 prioritized for the first time the serious games and gamification with two specific calls (ICT-21–14 and ICT-24–16) and, second, for the explosion of projects including these technologies in the past years (Adkins, 2017). These facts can be understood as a way to push the research to higher technology readiness levels (TRLs) and introducing the end-user in the co-creation and co-development along the value chain. Second, an additional limitation makes reference to the European focus of the projects, missing strong regional initiatives not identified and studied.

This paper has attempted to explore and define theoretically and empirically the characteristics found in the cross-fertilization of collaborative research projects, emphasizing which variables, and how, need to be stimulated to benefit more multidisciplinary consortia and accelerate the process of innovation.

Incidents of violence perpetrated through digital technology platforms or facilitated by these means have been reported, often in high-income countries. Very little scholarly attention has been given to the nature of technology-facilitated violence and abuse (TFVA) across sub-Saharan Africa (SSA) despite an explosion in the use of various technologies. We conducted a literature review to identify and harmonize available data relating to the types of TFVA taking place in SSA. This was followed by an online survey of young adults through the SHYad.NET forum to understand the nature of TFVA among young adults in SSA. Our literature review revealed various types of TFVA to be happening across SSA, including cyberbullying, cyberstalking, trolling, dating abuse, image-based sexual violence, sextortion, and revenge porn. The results of our online survey revealed that both young men and women experience TFVA, with the most commonly reported TFVA being receiving unwanted sexually explicit images, comments, emails, or text messages. Female respondents more often reported repeated and/or unwanted sexual requests online via email or text message while male respondents more often reported experiencing violent threats. Respondents used various means to cope with TFVA including blocking the abuser or deleting the abused profile on social media.

Automatically extracting stance information from natural language texts is a significant research problem with various applications, particularly after the recent explosion of data on the internet via platforms like social media sites. Stance detection system helps determine whether the author agree, against or has a neutral opinion with the given target. Most of the research in stance detection focuses on the English language, while few research was conducted on the Arabic language.

This paper aimed to address stance detection on Arabic tweets by building and comparing different stance detection models using four transformers, namely: Araelectra, MARBERT, AraBERT and Qarib. Using different weights for these transformers, the authors performed extensive experiments fine-tuning the task of stance detection Arabic tweets with the four different transformers.

The results showed that the AraBERT model learned better than the other three models with a 70% F1 score followed by the Qarib model with a 68% F1 score.

A limitation of this study is the imbalanced dataset and the limited availability of annotated datasets of SD in Arabic.

Provide comprehensive overview of the current resources for stance detection in the literature, including datasets and machine learning methods used. Therefore, the authors examined the models to analyze and comprehend the obtained findings in order to make recommendations for the best performance models for the stance detection task.

For the purpose of reducing the incidence of hazardous materials transport accident, eliminating the potential threats and ensuring their safety, aiming at the shortcomings in the process of current hazardous materials transportation management, this paper aims to construct the framework of hazardous materials transportation safety management system under the vehicle-infrastructure connected environment.

The system takes the intelligent connected vehicle as the main supporter, integrating GIS, GPS, eye location, GSM, networks and database technology.

By analyzing the transportation characteristics of hazardous materials, this system consists of five subsystems, which are vehicle and driver management subsystem, dangerous sources and hazardous materials management subsystem, route analysis and optimization subsystem, early warning and emergency rescue management subsystem, and basic information query subsystem.

Hazardous materials transportation safety management system includes omnibearing real-time monitoring, timely updating of system database, real-time generation and optimization of emergency rescue route. The system can reduce the transportation cost and improve the ability of accident prevention and emergency rescue of hazardous materials.

The purpose of this study is twofold; first, it aims to understand the underlying dynamics of the organizations behind the terrorist attacks, and second, to investigate the dynamics of terrorist organizations in relation to one another to detect whether there exist shared patterns of terror between different organizations.

To achieve this purpose, the researcher proposes a computational algorithm that extracts data from global terrorism database (GTD); calculates similarity indices between different terrorist groups; generates a network data file from the calculated indices; and apply network analysis techniques to the extracted data. The proposed algorithm includes applying SQL database codes for data extraction, building a tailored C# computer software to calculate similarity indices and generate similarity networks and using GEPHI software to visualize the generated network and calculate network metrics and measures.

Applying the proposed algorithm to Egypt, the results reveal different shared patterns of terror among different terrorist groups. This helps us in creating a terror landscape for terrorist groups playing in Egypt.

The importance of the study lies in that it proposes a new algorithm that combines network analysis with other data-manipulation techniques to generate a network of similar terror groups.

This chapter analyses the Norwegian authorities’ presence on Twitter during the 22 July 2011 terrorist attacks. Twitter activity by two official institutions is analysed in particular, namely, the blood bank at Oslo University Hospital and the Norwegian Police Security Services (PST). Our findings show that the Norwegian authorities were almost completely absent on Twitter during the critical hours of the terrorist attack, and that there was no coordination and synchronisation of communication from the authorities. This official silence allowed the diffusion of speculation and misinformation to take place; these were neither corrected nor addressed, as the analysed PST case shows. In contrast, the blood bank used Twitter to mobilise blood donors to address an acute problem: a shortage of blood to treat casualties. The chapter concludes by offering recommendations to the authorities for future major incidents.