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Women seafarers in Taiwan: policies, benefits, challenges, and bias in the data
No full textGender imbalance and equality have been highlighted in the global seafarer market. Taiwan relies heavily on shipping development and three container shipping companies (Evergreen, Yang Ming, Wai Hai Line) in Taiwan are ranked as top 11 in the world. To highlight the important contribution of women seafarers in the maritime industry, and add to the growing body of research in this area, this paper adopted in-depth interviews (n = 30) with both female (n = 24) and male (n = 6) seafarers to explore their perceptions of women seafarers regarding policies, benefits, and challenges. Key themes were barriers to employment such as company policies but also perceived benefits of employing women such as their ability with specific tasks such as administration and conciliation, aspects not highlighted before. Also, and uniquely, we identify a significant obstacle to achieving gender equality, and that is that the data gathered was biased; often delivered through the paradigm of the very problem itself: gender inequality and a male-biased environment. Nevertheless, and through identifying this obstacle, we make suggestions for engaging with and overcoming such biases in future work, and also help increase gender equality in the industry in line with United Nations Development Goals
Enhancing Automotive Intrusion Detection Systems with Capability Hardware Enhanced RISC Instructions-Based Memory Protection
Get PDFThe rapid integration of connected technologies in modern vehicles has introduced significant cybersecurity challenges, particularly in securing critical systems against advanced threats such as IP spoofing and rule manipulation. This study investigates the application of CHERI (Capability Hardware Enhanced RISC Instructions) to enhance the security of Intrusion Detection Systems (IDSs) in automotive networks. By leveraging CHERI’s fine-grained memory protection and capability-based access control, the IDS ensures the robust protection of rule configurations against unauthorized access and manipulation. Experimental results demonstrate a 100% detection rate for spoofed IP packets and unauthorized rule modification attempts. The CHERI-enabled IDS framework achieves latency well within the acceptable limits defined by automotive standards for real-time applications, ensuring it remains suitable for safety-critical operations. The implementation on the ARM Morello board highlights CHERI’s practical applicability and low-latency performance in real-world automotive scenarios. This research underscores the potential of hardware-enforced memory safety in mitigating complex cyber threats and provides a scalable solution for securing increasingly connected and autonomous vehicles. Future work will focus on optimizing CHERI for resource-constrained environments and expanding its applications to broader automotive security use cases
Self-care in social work: An imperative or beyond reach?
Get PDFIn recent years, the self-care of social workers has become a focus for research and practice in recognition of the demands of the social work role. As part of a research project to explore ways to embed self-care into a social work degree programme at a Scottish university, a narrative literature review was undertaken to examine existing research on self-care for social work students and practitioners. This article reports on the findings from this review, including the multiplicity of ways in which self-care is defined and conceptualized, how it is practised by social work students and practitioners, and the evidence base for identified approaches to self-care. Broader conceptualizations of self-care are explored, which encompass philosophical constructions of the ‘self’ and the impact of social and cultural norms on self-identity. It is argued that a cultural shift is required in the conceptualization and practice of self-care in social work to include collective and political approaches alongside individual strategies thereby promoting the social justice and anti-oppressive aims of the social work profession. Connections between self-care and ethical practice are highlighted, and further reinforce the need for self-care to be an imperative in social work
MA-Net: Resource-efficient multi-attentional network for end-to-end speech enhancement
No full textDeep Neural Networks (DNNs) have transformed speech enhancement (SE) by solving the complex relationships within speech signals through their multi-layered hierarchical representations. However, their computational demands remain a challenging problem. Self-attention has emerged as a key technique for capturing long-range dependencies in speech signals by measuring attention between vectors through scaled-dot products. Despite its widespread utility across various domains, self-attention encounters limitations when applied to SE. Specifically, its efficiency reduces in low signal-to-noise ratio (SNR) conditions due to its sensitivity to the scale of input vectors influenced by factors such as low SNRs. To address these challenges, we propose a resource-efficient Multi-Attention Network (MA-Net) speech enhancement model to effectively capture local and long-range dependencies in speech signals, while maintaining a low computational footprint. MA-Net integrates two fundamental modules: Spectral Temporal Hybrid Attention (STHA) and Dynamic Feedback Shuffle Attention (DFSA). The STHA module is designed to model long-range dependencies in spectral and temporal features by using hybrid self-attention (HSA). This mechanism computes attention weights between query () and key () vectors using dot-product and cosine similarity scores to mitigate the impact of scale variations in input vectors, enabling more consistent and reliable attention mechanisms. The DFSA module iteratively applies channel and spatial attention to dynamically refine feature representations by adjusting the weight of each iteration’s output based on input spectral features. Evaluations performed on two benchmark datasets (WSJ0-SI84 and VCTK+DEMAND) show that the MA-Net outperforms recent models in terms of SE performance at a considerably reduced computational complexity, with 0.92M parameters, 0.09 RTF, and 1.32G/s MACs. On the WSJ0-SI84 dataset, MA-Net improves PESQ, STOI, and SI-SDR by 1.26, 20.3%, and 9.76 dB over noisy mixtures, highlighting the usefulness of MA-Net in real-world SE conditions
WIND: A Wireless Intelligent Network Digital Twin for Federated Learning and Multi-Layer Optimization
Get PDFThe forthcoming wireless network is expected to support a wide range of applications, from supporting autonomous vehicles to massive Internet of Things (IoT) deployments. However, the coexistence of diverse applications under a unified framework presents several challenges, including seamless resource allocation, latency management, and systemwide optimization. Considering these requirements, this paper introduces WIND (Wireless Intelligent Network Digital Twin), a self-adaptive, self-regulating, and self-monitoring framework that integrates federated learning (FL) and multi-layer digital twins to optimize wireless networks. Unlike traditional digital twin (DT) models, the proposed framework extends beyond network modeling, incorporating both communication infrastructure and application-layer DTs to create a unified, intelligent, and contextaware wireless ecosystem. Besides, WIND utilizes local machine learning (ML) models at the edge node to handle low-latency resource allocation. At the same time, a global FL framework ensures long-term network optimization without centralized data collection. This hierarchical approach enables dynamic adaptation to traffic conditions, providing improved efficiency, security, and scalability. Moreover, the proposed framework is validated through a case study on federated reinforcement learning for radio resource management. Furthermore, the paper emphasizes the essential aspects, including the associated challenges, standardization efforts, and future directions opening the research in this domain
Toward 6G-Enabled URLLCs: Digital Twin, Open Ran, and Semantic Communications
No full textRecently, the concept of digital twin (DT), open radio access Network (O-RAN) and the adoption of semantic communications (SC) have been labeled as keystone technologies towards the deployment of 6G networks. This article aims to provide a comprehensive vision of how a DT-en-abled and SC based O-RAN architecture can sub-stantially contribute towards the achievement of ultra-reliable low-latency communications (URLLCs) requirements essential for the deployment of the innovative 6G-oriented services. A brief overviews about each single component are primarily provided. Subsequently, potential use cases and services delivered through such unified network framework are illustrated. Challenges and future research directions are also highlighted and discussed
Micro-mechanisms of digitalization-driven financing for renewable energy: Growing capital pools and shifting flows
No full textRecent facts from China suggest that the advancement of digitalization is altering the market expectations regarding renewable energy. Limited studies have offered evidence encompassing the stock effect of digitalization that enhanced corporate financing and the flow effect that initiated speculative behavior. However, a comprehensive discourse remains insufficient. This paper investigates the synergetic effects of digitalization's stock and flow on renewable energy financing, employing the business data of all listed companies in China from 2003 to 2023. The results demonstrate that: (1) Digitalization's stock has expanded the potential fund pool for renewable energy financing, yet it is challenging to influence the flow of funds; digitalization's flow has triggered a flood of funds into the renewable energy industry, but this relies on the new investors attracted by the stock. (2) The synergetic effect governs the systematic influence of digitalization on renewable energy financing and mitigates the measurement bias when considering only a single effect. (3) We further contemplate the indirect effects of renewable energy market expansion, technological progress, and global energy market fluctuations, alleviating concerns regarding the omitted variable bias. The results of the differential regression and generalized method of moments also indicate the robustness of the conclusion
Discrete Element Study of Particle Size Distribution Shape Governing Critical State Behavior of Granular Material
Get PDFGranular soil is a porous medium composed of particles with different sizes and self-similar structures, exhibiting fractal characteristics. It is well established that variations in these fractal properties, such as particle size distribution (PSD), significantly influence the mechanical behavior of the soil. In this paper, a three-dimensional (3D) Discrete Element Method (DEM) is applied to study the mechanical and critical-state behavior of the idealized granular assemblages, in which various PSD shape parameters are considered, including the coefficient of uniformity (Cu), the coefficient of curvature (Cc), and the coefficient of size span (Cs). In addition, the same PSDs but with different mean particle sizes (D50) are also employed in the numerical simulations to examine the particle size effect on the mechanical behavior of the granular media. Numerical triaxial tests are carried out by imposing axial compression under constant mean effective pressure conditions. A unique critical-state stress ratio in p′-q space is observed, indicating that the critical friction angle is independent of the shape of the PSD. However, in the e-p′ plane, the critical state line (CSL) shifts downward and rotates counterclockwise, as the grading becomes more widely distributed, i.e., the increasing coefficient of span (Cs). Additionally, a decrease in the coefficient of curvature (Cc) would also move the CSL downward but with negligible rotation. However, it is found that the variations in the mean particle size (D50) and coefficient of uniformity (Cu) do not affect the position of the CSL in the e-p′ plane. The numerical findings may shed some light on the development of constitutive models of sand that undergo variations in the grading due to crushing and erosion, and address fractal problems related to micro-mechanics in soils
Confronting the smart city governance challenge
No full textGovernance inefficiencies threaten the potential of smart city projects to deliver equitable urban transformations. Current strategies often hinder implementation, and risk harmful technological effects on communities. Tackling this challenge demands urgent reforms to better integrate scientific insights into smarter governance practices
Predictor Factors Associated With Hazardous Drug Safe Handling Precautions Across a UK Oncology Nurse Sample and Implications for Novel Treatments
Get PDFObjectivesThe development and use of novel systemic anticancer therapy (SACT) treatments are advancing rapidly. While cytotoxic drugs have traditionally been the cornerstone of treatment, they are increasingly used alongside novel agents. This study aims to assess factors affecting adherence to safe-handling precautions, enhance safety protocols, and minimize potential occupational exposure to hazards in clinical environments, increasing their capacity for novel treatments.MethodsCross-sectional, online survey of oncology nurses across the UK who handled SACT. Participants were asked to complete the Factors Predicting Use of Hazardous Drug Safe-Handling Precautions Questionnaire. Descriptive analysis, Spearman rank correlation coefficients, and regression analysis were performed to determine the predictors of precautionary use when handling HDs.FindingsAnalysis of (n = 675) participants revealed high knowledge of exposure, high self-efficacy, low perceived barriers, moderate perceived risks, high interpersonal influence, low conflict of interest and moderate safety climate in the workplace. The analysis of the data also indicated weak positive correlations between age and knowledge (rs = 0.093), self-efficacy (rs = 0.103) and safe-handling scores (rs = 0.082); the age of the participants has a weak negative correlation to perceived barriers (rs = –0.141), conflict of interest (rs = –0.116), and workplace safety climate(rs = –0.116). Notably, safe handling scores showed no significant correlation with other theoretical predictors. Comparison between government and private sector nurses (n = 76) demonstrated higher patient volumes F (15.807, 74), P < .001 and significantly lower safe handling scores in the government settings F (4.135, 74) P < .05.ConclusionsNurse-patient ratios between government and private sector settings predict global safe-handling precautions.Implications for practiceNovel treatments for nurse-patient ratios are essential, as new therapies and schedules further create additional workload pressures that may reduce safe handling practices
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