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Fire smoke detection in petrochemical plant can prevent fire and ensure production safety and life safety. The purpose of this paper is to solve the problem of missed detection and false detection in flame smoke detection under complex factory background.

This paper presents a flame smoke detection algorithm based on YOLOv5. The target regression loss function (CIoU) is used to improve the missed detection and false detection in target detection and improve the model detection performance. The improved activation function avoids gradient disappearance to maintain high real-time performance of the algorithm. Data enhancement technology is used to enhance the ability of the network to extract features and improve the accuracy of the model for small target detection.

Based on the actual situation of flame smoke, the loss function and activation function of YOLOv5 model are improved. Based on the improved YOLOv5 model, a flame smoke detection algorithm with generalization performance is established. The improved model is compared with SSD and YOLOv4-tiny. The accuracy of the improved YOLOv5 model can reach 99.5%, which achieves a more accurate detection effect on flame smoke. The improved network model is superior to the existing methods in running time and accuracy.

Aiming at the actual particularity of flame smoke detection, an improved flame smoke detection network model based on YOLOv5 is established. The purpose of optimizing the model is achieved by improving the loss function, and the activation function with stronger nonlinear ability is combined to avoid over-fitting of the network. This method is helpful to improve the problems of missed detection and false detection in flame smoke detection and can be further extended to pedestrian target detection and vehicle running recognition.

This paper aims to conduct an interdisciplinary systematic literature review (SLR) of fake news research and to advance the socio-technical understanding of digital information practices and platforms in business and management studies.

The paper applies a focused, SLR method to analyze articles on fake news in business and management journals from 2010 to 2020.

The paper analyzes the definition, theoretical frameworks, methods and research gaps of fake news in the business and management domains. It also identifies some promising research opportunities for future scholars.

The paper offers practical implications for various stakeholders who are affected by or involved in fake news dissemination, such as brands, consumers and policymakers. It provides recommendations to cope with the challenges and risks of fake news.

The paper discusses the social consequences and future threats of fake news, especially in relation to social networking and social media. It calls for more awareness and responsibility from online communities to prevent and combat fake news.

The paper contributes to the literature on information management by showing the importance and consequences of fake news sharing for societies. It is among the frontier systematic reviews in the field that covers studies from different disciplines and focuses on business and management studies.

In lieu of a cure, the idea that dementia might be preventable through risk-factor moderation has latterly gained popularity. Prevention research is an evolving field that will likely undergo significant shifts in the near future. This paper aims to engage with that future as it is imagined in the present.

This study explores the futures envisaged by dementia prevention researchers in the UK, based on interviews with six practitioners at the forefront of the field.

Participants foresaw a pivot away from “dementia prevention” toward “brain health”, and advocated for blended policy, community and lifestyle interventions. They were excited by the prospects for a lifecourse dementia hypothesis to inform new interventions but uncomfortable with the ethics of early intervention.

These findings complicate simplistic depictions of prevention researchers as pursuing responsibilised lifestyle approaches.

The application of three-dimensional (3D) printing technology in construction projects is of increasing interest to researchers and construction practitioners. Although the application of 3D printing technology at various stages of the project lifecycle has been explored, few studies have identified the relative importance of critical success factors (CSFs) for implementing 3D printing technology in construction projects. To address this research gap, this study aims to explore the academics (i.e. researchers) and construction practitioners’ perspectives on CSFs for implementing 3D printing technology in construction projects.

To do this, a questionnaire was administered to participants (i.e. academics and construction practitioners) with knowledge and expertise in 3D printing technology in construction projects. The collected data were analysed using mean score ranking, normalization and rank agreement analysis to identify CSFs and determine the consistency of the ranking of CSFs between academics and construction practitioners. In addition, exploratory factor analysis was used to identify the relationships and underlying constructs of the measured CSFs.

Through a rank agreement analysis of the collected data, 11 CSFs for implementing 3D printing technology were retrieved (i.e. 17% agreement), indicating a diverse agreement in the ranking of the CSFs between academics and construction practitioners. In addition, the results show three key components of CSFs including “production demand enabling CSFs”, “optimize the construction process enabling CSFs” and “optimized design enabling CSFs”.

This study highlights the feasibility of implementing the identified CSFs for 3D printing technology in construction projects, which not only serves as a reference for other researchers but also increases construction practitioners’ awareness of the practical benefits of implementing 3D printing technology in construction projects. Specifically, it would optimize the construction lifecycle processes, enhance digital transformation and promote sustainable construction projects.

People in prisons have a high prevalence of poly-traumatisation throughout their life span. The behavioural and emotional sequalae of trauma are likely to be managed across the whole organisation. However, there is still a lack of clarity about the key components of a trauma-informed approach within the custodial context. This study aimed to gather in-depth knowledge of staff views on the components of an optimal trauma pathway in a prison and the organisational factors that influence its implementation.

The authors’ research design is qualitative, involving in-depth, semi-structured interviews with eight members of staff from different professional backgrounds at a single prison in the UK that houses sentenced and remand prisoners. Data was analysed using reflexive thematic analysis.

Three super-ordinate themes were identified within the data. Firstly, components of a trauma-informed pathway included sub-themes of asking about what has happened and knowing how to respond; providing specialist approaches; enabling residents to cope; screening and detection; and a compassionate relational approach. Secondly, organisational factors were associated with sub-themes of culture and leadership, resources and systems and processes. Thirdly, staff factors were associated with sub-themes of skills development and training, staff well-being and support and staff attitudes.

Post-traumatic stress disorder (PTSD) and complex PTSD in prisons are under-detected, and there are complex psychosocial factors within prisons that mediate the effectiveness of psychological therapies.

To the best of the authors’ knowledge, this study represents the first exploration of staff perspectives on the components of a trauma-informed pathway within custodial settings. Future directions should involve the piloting and evaluation of the components of the trauma-informed pathway, with a focus on longer-term outcomes and exploration of the organisational factors that impact on effectiveness.

The purpose of this paper is to figure out how authoritarian regimes conduct crisis management through application of technology, institutions and people.

By means of a literature review, this paper briefly reviews the digital governance of authoritarianism and its approach in crisis management. Then, a case study with empirical analysis is conducted to explain how an authoritarian regime would perceive and manage crises in the digital era.

China’s response towards COVID-19 was mainly based on digitalised grid management. Government’s perception of the crisis directly influences directions of institutions, while technology is developed, applied and iterated with the needs of institutions, rather than the public interests. And for the general public, the level of trust in the government directly affects the acceptance of technology.

Previous studies on crisis management of authoritarian governments in the digital era have mostly been conducted from a techno-ethical perspective. However, this paper verifies that the use of technology in crisis management requires involvement of institutions and public.

The natural control, feedback, stimuli and protection of these subsequent principles founded this project. Via properly conducted experiments, a multilayer computer rehabilitation system was created that integrated natural interaction assisted by electroencephalogram (EEG), which enabled the movements in the virtual environment and real wheelchair. For blind wheelchair operator patients, this paper involved of expounding the proper methodology. For educating the value of life and independence of blind wheelchair users, outcomes have proven that virtual reality (VR) with EEG signals has that potential.

Individuals face numerous challenges with many disorders, particularly when multiple dysfunctions are diagnosed and especially for visually effected wheelchair users. This scenario, in reality, creates in a degree of incapacity on the part of the wheelchair user in terms of performing simple activities. Based on their specific medical needs, confined patients are treated in a modified method. Independent navigation is secured for individuals with vision and motor disabilities. There is a necessity for communication which justifies the use of VR in this navigation situation. For the effective integration of locomotion besides, it must be under natural guidance. EEG, which uses random brain impulses, has made significant progress in the field of health. The custom of an automated audio announcement system modified to have the help of VR and EEG for the training of locomotion and individualized interaction of wheelchair users with visual disability is demonstrated in this study through an experiment. Enabling the patients who were otherwise deemed incapacitated to participate in social activities, as the aim was to have efficient connections.

To protect their life straightaway and to report all these disputes, the military system should have high speed, more precise portable prototype device for nursing the soldier health, recognition of solider location and report about health sharing system to the concerned system. Field programmable gate array (FPGA)-based soldier’s health observing and position gratitude system is proposed in this paper. Reliant on heart rate which is centered on EEG signals, the soldier’s health is observed on systematic bases. By emerging Verilog hardware description language (HDL) programming language and executing on Artix-7 development FPGA board of part name XC7ACSG100t the whole work is approved in a Vivado Design Suite. Classification of different abnormalities and cloud storage of EEG along with the type of abnormalities, artifact elimination, abnormalities identification based on feature extraction, exist in the segment of suggested architecture. Irregularity circumstances are noticed through developed prototype system and alert the physically challenged (PHC) individual via an audio announcement. An actual method for eradicating motion artifacts from EEG signals that have anomalies in the PHC person’s brain has been established, and the established system is a portable device that can deliver differences in brain signal variation intensity. Primarily the EEG signals can be taken and the undesirable artifact can be detached, later structures can be mined by discrete wavelet transform these are the two stages through which artifact deletion can be completed. The anomalies in signal can be noticed and recognized by using machine learning algorithms known as multirate support vector machine classifiers when the features have been extracted using a combination of hidden Markov model (HMM) and Gaussian mixture model (GMM). Intended for capable declaration about action taken by a blind person, these result signals are protected in storage devices and conveyed to the controller. Pretending daily motion schedules allows the pretentious EEG signals to be caught. Aimed at the validation of planned system, the database can be used and continued with numerous recorded signals of EEG. The projected strategy executes better in terms of re-storing theta, delta, alpha and beta complexes of the original EEG with less alteration and a higher signal to noise ratio (SNR) value of the EEG signal, which illustrates in the quantitative analysis. The projected method used Verilog HDL and MATLAB software for both formation and authorization of results to yield improved results. Since from the achieved results, it is initiated that 32% enhancement in SNR, 14% in mean squared error (MSE) and 65% enhancement in recognition of anomalies, hence design is effectively certified and proved for standard EEG signals data sets on FPGA.

The proposed system can be used in military applications as it is high speed and excellent precise in terms of identification of abnormality, the developed system is portable and very precise. FPGA-based soldier’s health observing and position gratitude system is proposed in this paper. Reliant on heart rate which is centered on EEG signals the soldier health is observed in systematic bases. The proposed system is developed using Verilog HDL programming language and executing on Artix-7 development FPGA board of part name XC7ACSG100t and synthesised using in Vivado Design Suite software tool.

Identifying autism spectrum disorder (ASD) in children’s early years significantly impacts their academic performance and future life. It allows them to receive special support services and the required early intervention. Preschool teachers spend considerable time with their students, which allows them to observe their behaviors in different settings like classrooms and playgrounds. However, teachers need to be knowledgeable of ASD early assessment to detect them. Whereas, all well-known ASD assessment tools are designed for populations from different cultures than the Gulf Cooperation Councils' (GCC) culture. This study emphasizes the importance of preschool age, from 3 to 5, in indicating children's early signs of ASD. This paper aims to indicate the early signs of ASD in preschool children in the UAE as a model for other GCC countries.

A qualitative method consisting of interviews with preschool teachers and the ASD children’s parents was conducted to investigate the ASD early symptoms in children.

The findings of the study show that there is a direct connection between the opinions expressed by preschool teachers and the parents of children with ASD (Autism Spectrum Disorder). These results also highlight the presence of early indications of ASD among preschool-aged children in the United Arab Emirates, such as difficulties in communication, repetitive actions, delayed speech, excessive focus on tablets, trouble paying attention, hyperactivity, sleep problems, and aggressive behavior.

The outcomes suggest a strong connection between the feedback from preschool teachers and the parents of children with ASD. The study uncovers initial indications of ASD in preschool-aged children from the United Arab Emirates, such as difficulties in communication, repetitive actions, delayed speech, excessive fascination with tablets, problems with attention, hyperactivity, sleep disturbances, and aggressive behavior.

Maintenance represents an indispensable role in the productive sector of the steel industry. The increasing use of operating with a high level of precision makes hydraulic systems one of the issues that require a high level of attention. This study aims to explore an empirical investigation for decreasing the occurrences of corrective maintenance of hydraulic systems in the context of Lean 4.0.

The maintenance model is developed based on action-research methodology through an empirical investigation, with nine stages. This approach aims to build a scenario to analyze and interpret the occurrences, seeking to implement and evaluate the actions to be performed. The undertaken initiatives demonstrate that this approach can be applied to optimize the maintenance of an organization.

The main contribution of this paper is to demonstrate that the applied method allows the overviewing results, with a qualitative approach concerning the maintenance actions and management processes to be considered, allowing a holistic understanding and contributing to the current literature. The results also indicated that Lean 4.0 has direct and mediating effects on maintenance performance.

This research intends to propose an evaluation framework with an interdimensional linkage between action research methodology and Lean 4.0, to explore an empirical investigation and contributing to understanding the actions to reduce the occurrences of hydraulic systems corrective maintenance in a production line in the steel industry.

This paper aims to explore the antecedents and consequences of service chain flexibility (SCF) in healthcare service delivery.

A structural model was developed based on a literature review. A 29-indicator questionnaire was circulated among service providers in the healthcare system across India, and 253 valid responses were received, corresponding to a response rate of 46%. The research model was assessed using a cross-sectional research design, and the data were analyzed by structural equation modeling using analysis of moment structures (AMOS) software.

Service orientation (SO), technology integration (TI), knowledge sharing (KS) and supply chain integration (SCI) were identified as antecedents of SCF, the consequence of which is responsiveness in service delivery (RSD). Furthermore, patient-centered care moderates the relationship between SCF and RSD.

This paper highlights the impact of SCF on RSD in healthcare organizations. Consideration of the four constructs of SO, TI, KS and SCI as antecedents of SCF and, in turn, RSD may be one of the limitations. Future work may identify other theoretical constructs with potential impacts on SCF and RSD. Furthermore, eight months for data collection could have resulted in early-late response bias. This study was operationalized in India and may reflect political, economic, social, technological, environmental and legal factors unique to India.

The study provides suggestions to practitioners for building RSD by leveraging SO, TI, KS and SCI in flexibility-driven service chain processes. Recognizing the relationships among these constructs can aid in the timely formulation of corrective actions and patient-centric policies.

This paper highlights how focusing on a SCF can promote RSD. This understanding may aid the design of processes that develop patient-centricity and deliver health as a social good in an effective manner.

The empirical evidence from this study can help hospitals integrate and build flexibility in their functions, thus enabling them to deliver responsiveness in care.