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The potential of vehicle ad hoc networks (VANETs) to improve driver and passenger safety and security has made them a hot topic in the field of intelligent transportation systems (ITSs). VANETs have different characteristics and system architectures from mobile ad hoc networks (MANETs), with a primary focus on vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication. But protecting VANETs from malicious assaults is crucial because they can undermine network security and safety.

The black hole attack is a well-known danger to VANETs. It occurs when a hostile node introduces phony routing tables into the network, potentially damaging it and interfering with communication. A safe ad hoc on-demand distance vector (AODV) routing protocol has been created in response to this issue. By adding cryptographic features for source and target node verification to the route request (RREQ) and route reply (RREP) packets, this protocol improves upon the original AODV routing system.

Through the use of cryptographic-based encryption and decryption techniques, the suggested method fortifies the VANET connection. In addition, other network metrics are taken into account to assess the effectiveness of the secure AODV routing protocol under black hole attacks, including packet loss, end-to-end latency, packet delivery ratio (PDR) and routing request overhead. Results from simulations using an NS-2.33 simulator show how well the suggested fix works to enhance system performance and lessen the effects of black hole assaults on VANETs.

All things considered, the safe AODV routing protocol provides a strong method for improving security and dependability in VANET systems, protecting against malevolent attacks and guaranteeing smooth communication between cars and infrastructure.

This paper presents a review of the state of the art on the application of blockchain and smart contracts to the peer-review process of scientific papers. The paper seeks to analyse how the main characteristics of the existing blockchain solutions in this field to detect opportunities for the improvement of future applications.

A systematic review of the literature on the subject was carried out in three databases recognized by the research community (IEEE Xplore, Scopus and Web of Science) and the Frontiers in Blockchain journal. A total of 1,967 articles were initially found, and after the exclusion process, the 26 remaining articles were classified according to the following dimensions: System Type, Open Access, Review Type, Reviewer Incentive, Token Economy, Blockchain Access, Blockchain Identification, Blockchain Used, Paper Storage, Anonymity and Maturity of the solution.

Results show that the solutions are normally concerned on offering incentives to the reviewers' work (often monetary). Other common general preferences among the solutions are the adoption of open reviews, the use of Ethereum, the implementation of publishing ecosystems and the use of InterPlanetary File System to the storage of the papers.

There are currently no studies covering the main aspects of blockchain solutions in the field of scientific peer review. The present study provides an overall review of the topic, summarizing important information on the current research and helping new adopters to develop solutions grounded on the existing literature.

GraphQL is a new Open API specification that allows clients to send queries and obtain data flexibly according to their needs. However, a high-complexity GraphQL query may lead to an excessive data volume of the query result, which causes problems such as resource overload of the API server. Therefore, this paper aims to address this issue by predicting the response data volume of a GraphQL query statement.

This paper proposes a GraphQL response data volume prediction approach based on Code2Vec and AutoML. First, a GraphQL query statement is transformed into a path collection of an abstract syntax tree based on the idea of Code2Vec, and then the query is aggregated into a vector with the fixed length. Finally, the response result data volume is predicted by a fully connected neural network. To further improve the prediction accuracy, the prediction results of embedded features are combined with the field features and summary features of the query statement to predict the final response data volume by the AutoML model.

Experiments on two public GraphQL API data sets, GitHub and Yelp, show that the accuracy of the proposed approach is 15.85% and 50.31% higher than existing GraphQL response volume prediction approaches based on machine learning techniques, respectively.

This paper proposes an approach that combines Code2Vec and AutoML for GraphQL query response data volume prediction with higher accuracy.

Demonstrate proof-of-concept for conducting NFL Draft trades on a blockchain network using smart contracts.

Using Ethereum smart contracts, the authors model several types of draft trades between teams. An example scenario is used to demonstrate contract interaction and draft results.

The authors show the feasibility of conducting draft-day trades using smart contracts. The entire negotiation process, including side deals, can be conducted digitally.

Further work is required to incorporate the full-scale depth required to integrate the draft trading process into a decentralized user platform and experience.

Cutting time for the trade negotiation process buys decision time for team decision-makers. Gains are also made with accuracy and cost.

Full-scale adoption may find resistance due to the level of fan involvement; the draft has evolved into an interactive experience for both fans and teams.

This research demonstrates the new application of smart contracts in the inter-section of sports management and blockchain technology.

The credit of agricultural product quality and safety reflects the ability of the main actors involved in the supply chain to provide reliable agricultural products to consumers. To fundamentally solve the problem of agricultural product quality and safety, it is worth studying how to make the credit awareness and integrity self-discipline of the supply chain agriculture-related subjects strengthened and the role and value of credit supervision given full play. Starting from the application of blockchain in the agricultural product supply chain, this paper aims to investigate the main factors affecting the credit regulation of agricultural product quality.

Using the DEMATEL-ISM (decision-making trial and evaluation laboratory–interpretative structural modeling) method, we analyze the credit influencing factors of agricultural quality and safety empowered by blockchain technology, find the causal relationship between the crucial influencing factors and deeply explore the hierarchical transmission relationship between the influencing factors. Then, the path analysis in structural equation modeling is utilized to verify and measure the significance and effect value of the transmission relationship among the crucial influencing factors of credit regulation.

The results show that the quality and safety credit regulation of agricultural products is influenced by a combination of direct and deep influencing factors. Long-term stable cooperative relationship, Quality and safety credit evaluation, Supply chain risk control ability, Quality and safety testing, Constraints of the smart contract are the main influence path of blockchain embedded in agricultural product supply chain quality and safety credit supervision.

Credit supervision is an important means to improve the ability and level of social governance and standardize the market order. From the perspective of blockchain embedded in the agricultural supply chain, the regulatory body is transformed from the product body to the supply chain body. Take the credit supervision of supply chain subjects as the basis of agricultural product quality supervision. With the help of blockchain technology to improve the effectiveness of agricultural product quality and safety credit supervision, credit supervision is used to constrain and incentivize the behavior of agricultural subjects.

Public safety (communicators; e.g. 9-1-1, police, fire and ambulance call-takers and dispatchers), like many other public safety personnel (e.g. police, paramedics), (re)suffer operational stress injuries (OSIs) that are too often hidden and at a prevalence higher than the general population. Unfortunately, there are very little data for OSI rates in Canadian communicators. To the authors’ knowledge, this is the only pan-Canadian study focusing on organizational culture, and its potential influence on OSIs, within the communicator context.

The authors conducted a 179-item online survey of Canadian communicators comprising 17 validated screenings for occupational stress injuries and symptoms and four open-ended questions relating to their agency's organizational culture. The authors thematically analysed participants' open-ended responses and their screening scores.

A semi-grounded thematic approach revealed that managers and supervisors were significant contributors to negative perceptions (n = 165) of organizational culture, potentially resulting in or worsening existing OSIs. Specifically, leadership was viewed as ineffective, inconsistent, unsupportive, abusive and toxic, with limited understanding of communicator roles. Communicators described feeling devalued, particularly when leaders fail to recognize communicator OSIs, which can perpetuate stigma. Conversely, positive leaders (n = 24) were described as supportive, communicative and encouraging.

The findings suggest that while leadership behaviours are a key factor in employee well-being, it varies considerably across agencies, impacting treatment-seeking behaviours. The authors’ new understandings of leaders' roles in OSIs may help reduce the frequency and severity of communicator OSIs, helping ensure that emergency services are delivered to Canadians.

The purpose of this paper is to construct an event-triggered finite-time fault-tolerant formation tracking controller, which can achieve a time-varying formation control for multiple unmanned aerial vehicles (UAVs) during actuator failures and external perturbations.

First, this study developed the formation tracking protocol for each follower using UAV formation members, defining the tracking inaccuracy of the UAV followers’ location. Subsequently, this study designed the multilayer event-triggered controller based on the backstepping method framework within finite time. Then, considering the actuator failures, and added self-adaptive thought for fault-tolerant control within finite time, the event-triggered closed-loop system is subsequently shown to be a finite-time stable system. Furthermore, the Zeno behavior is analyzed to prevent infinite triggering instances within a finite time. Finally, simulations are conducted with external disturbances and actuator failure conditions to demonstrate formation tracking controller performance.

It achieves improved performance in the presence of external disturbances and system failures. Combining limited-time adaptive control and event triggering improves system stability, increase robustness to disturbances and calculation efficiency. In addition, the designed formation tracking controller can effectively control the time-varying formation of the leader and followers to complete the task, and by adding a fixed-time observer, it can effectively compensate for external disturbances and improve formation control accuracy.

A formation-following controller is designed, which can handle both external disturbances and internal actuator failures during formation flight, and the proposed method can be applied to a variety of formation control scenarios and does not rely on a specific type of UAV or communication network.

The paper aims to provide a critical review of how variations in the conceptualization and contextualization of hate crime across US cities might impact how their individual law enforcement agencies collect hate crime data. Media reports and political discourses present hate crime as a prevalent problem in the USA. However, this representation of hate crime in the public sphere is not reflected in the relatively low national numbers of hate crimes published annually by the Federal Bureau of Investigation.

Drawing primarily on the national hate crime data for the period 2008–2018, this author conducted a secondary research study of the concept, context, extent and law enforcement collection of hate crime data in five cities in the USA.

This paper is a product of some of the findings of the study, which include the definition of hate crime at the federal, state and city levels and the contextualization of hate crimes at these levels. The findings show inconsistencies in how the five cities and associated law enforcement agencies conceptualize hate crime and in how they collect and report hate crime data at local and national levels.

Through its analysis of how five US cities and the associated law enforcement agencies interpret and respond to hate crime data collection, with recommendations of best practices for hate crime data collection by law enforcement agencies, the paper contributes to the academic and nonacademic debate on hate crime.

In the information and technology age, where the “physical” world is merged with the “digital” world, the nature of social conditions, relations, citizenship and the flow of information has shifted from a moral and legal approach to a digital approach. Nowadays, the functioning, dissemination, conduct and governance of organisations and their members are regulated by techno-ethical and digital principles. Drawing on social cognitive theory, the study hypothesises that techno-ethical orientation predicts corporate ethical values (CEV) through the moderation of digital citizenship behaviour (DC). The study further proposes that each dimension of DC: online respect (OR) and online civic engagement (OCE), moderates the hypothesised relationship.

546 respondents from India participated in the study. The responses were captured using structured and well-established questionnaires. The analysis was performed using robust measures of correlation, regression, reliability (Cronbach’s alpha and composite reliability) and validity (convergent and discriminant validity). The moderation influence of DC was tested and analysed using structural equation modelling (SEM) Analysis of Moment Structures (AMOS).

The regression findings of the study revealed that the techno-ethical orientation positively predicts the CEV. R-square values showed a 24.1% variation in corporate ethical value was explained by techno-ethical orientation. It indicates that a positive techno-ethical orientation establishes the ethical context and corporate values. Besides, the moderation analysis using SEM AMOS indicates that at both low and high levels of OR and OCE, the relationship between techno-ethical orientation and CEV is positive and significant.

This study demonstrates a new facet of technology ethics that promotes the institutionalisation of CEV through DC. This study is the first to explore the interaction between techno-ethical orientation and CEV. Even though various former factors concerning ethical conduct have been examined, the results of the techno-ethical conduct of employees within the scope of an organisation have not been explored so far.

This study aims to explore the dissemination and evolutionary path of online public opinion from a crisis management perspective. By clarifying the influencing factors and dynamic mechanisms of online public opinion dissemination, this study provides insights into attenuating the negative impact of online public opinion and creating a favorable ecological space for online public opinion.

This research employs bibliometric analysis and CiteSpace software to analyze 302 Chinese articles published from 2006 to 2023 in the China National Knowledge Infrastructure (CNKI) database and 276 English articles published from 1994 to 2023 in the Web of Science core set database. Through literature keyword clustering, co-citation analysis and burst terms analysis, this paper summarizes the core scientific research institutions, scholars, hot topics and evolutionary paths of online public opinion crisis management research from both Chinese and international academic communities.

The results show that the study of online public opinion crisis management in China and internationally is centered on the life cycle theory, which integrates knowledge from information, computer and system sciences. Although there are differences in political interaction and stage evolution, the overall evolutionary path is similar, and it develops dynamically in the “benign conflict” between the expansion of the research perspective and the gradual refinement of research granularity.

This study summarizes the research results of online public opinion crisis management from China and the international academic community and identifies current research hotspots and theoretical evolution paths. Future research can focus on deepening the basic theories of public opinion crisis management under the influence of frontier technologies, exploring the subjectivity and emotionality of web users using fine algorithms and promoting the international development of network public opinion crisis management theory through transnational comparison and international cooperation.