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Assessing numerical error bound of classic grey prediction model: An application to the transport performance of China’s civil aviation industry
No full textThe file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.Although grey system models have been developed and applied successfully to various socio-economic and engineering problems for several decades, the algorithm stability problem of these models has never been investigated. This paper introduces a method to estimate the error bounds of algorithms used in the classic grey prediction model. To reduce the complex calculation in finding the model error bounds, equivalent but simple estimation models are presented. An algebraic optimization technique for the solution processes of the proposed mathematic models is then provided. The backward error bound model is then extended to the other two commonly used linear regression forecasting models and the similarities and differences between them are explored. Finally, the proposed method is applied to the prediction of four key transportation performance indicators for China’s civil aviation industry. The case study considers not only the traditional accuracy criteria, but also the stability of prediction results in model optimization. The robustness of prediction methods with different types of noise interference and weighting preference scenarios are tested. It is found that model solving methods influence the error bounds, but smaller prediction errors do not necessarily guarantee better backward stability or applicability of the prediction model. Methods described in this paper make it possible to measure numerically the accuracy of any alleged solution of the classic grey prediction model and other linear regression models and provide an objective, quantitative approach to evaluating the effectiveness of information processing in different sample disturbances situations
Self-learning brainstorm optimization for synchronization of operations and maintenance toward dual resource-constrained flexible job shops
No full textThe file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.In semi-automated flexible job shop manufacturing scenarios such as furniture customization and circuit board assembly, machine and worker resources need to be flexibly assigned to the processing of each operation, to improve the efficiency of human-machine collaboration and reduce the makespan. Driven by the practical need, the dual resource-constrained flexible job shop scheduling problem (DRCFJSP) has gradually attracted attention from the academic community. However, preventive maintenance (PM) of machines as a key constraint tends to be overlooked in previous research. In this study, a synchronization optimization of the DRCFJSP and PM scheduling is proposed and a joint decision-making model is established, to strike a balance between flexible job shop operations and maintenance. A self-learning brainstorm optimization algorithm (SLBOA) is developed to solve the model. In the SLBOA, an adaptive K-means algorithm based on the silhouette method is employed for flexible clustering, and four global update strategies are adaptively selected using the Q-learning algorithm to facilitate an effective interaction of individuals between different clusters. Furthermore, two knowledge-based local search methods are used to enhance the exploration of elite solutions within the necessary neighborhood structure. Experimental results show that the SLBOA outperforms four state-of-the-art algorithms in solving the proposed DRCFJSP with PM
Corrosion Atlas Case Studies
No full textCorrosion Atlas Case Studies: 2025 Edition gives engineers expedient corrosion solutions for common industrial equipment, no matter the industry. Providing a purely operational level view, this reference is designed as concise case studies categorized by material. It includes content surrounding the phenomenon, equipment appearance (supported by a color image), time of service, conditions where the corrosion occurred, cause, and suggested remedies within each case study. Rounding out with an introductory, foundational layer of corrosion principles, this book delivers what is needed to solve equipment corrosion problems. Finally, additional reference listings for deeper understanding beyond the practical elements are also included
Path Invariance of a Quadrotor System under Cyber Attacks with Theoretical Guarantees
No full textThe file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.This paper presents a path-following controller for a quadrotor system to guarantee safe maneuvers, in terms of forward path invariance, in the presence of cyber-physical attacks. We assume that an adversarial agent can control any one of the rotors through a false data injection (FDI) type of attack. A feedback controller is designed using transverse feedback linearization which guarantees that the system follows a class of smooth curves under FDI attacks. Our proposed controller is computationally efficient, with a closed-form analytical expression, that not only mitigates the effect of bounded malicious signal but also ensures mission success. We provide theoretical guarantees of forward path invariance under FDI attacks with realistic assumptions and demonstrate the effectiveness of our approach through simulation
Refusal: lingering, stillness, and rest as collective action
No full textThis was a 20-minute conference paper given at TaPRA, the Theatre and Performance Research Association, at University of Warwick, UK, in August 2025. This paper was part of the Documenting Performance working group.Black Power Naps (2015- ), initiated by artists Navild Acosta and Sosa, are interactive installations that invite participants to practise rest amid cushions, blankets, and calming soundscapes. It is predicated on the ‘sleep gap’ experienced by Black people in the US, who routinely get insufficient sleep compared to their white counterparts. The project advocates for rest as a resistant act and pushes back against histories and practices that otherwise exhaust or seek to control Black subjects. In a Black Power Naps installation at MoMA in 2023, Black British artist Heather Agyepong was removed after confronting a white visitor who was laughing in the space. Agyepong’s act of refusal within and her removal from a space dedicated to Black rest made hyper-visible the systemic and institutional structures against which Black Power Naps pushes and, importantly, the labour involved in that refusal. Drawing from Tricia Hersey’s Rest Is Resistance manifesto (2022), which proposes rest as an act of resistance and means of reclaiming power, and Miggy Esteban’s scholarship and movement practice (2023), which resists conceptions of stillness as a state of nonbeing, I ask: How are subjects constructed, shaped, and policed by practices of lingering, stillness, and rest? How are acts of lingering, stillness, and rest in art and public spaces framed as political? And what does the visibility of the labour required for such acts afford for subjects, both individual and collective? In this Working Group, I am interested in exploring Black Power Naps and rest, stillness, and lingering more broadly as modes or spaces of relation which practice holding, listening, imagining, and indeed acting collectively. In this regard, stillness, rest, and lingering are practices of both presence and preservation (in the sense of self-preservation and preserving energy), which not only hold the potential for collective action but also enact it
Cities and Governance for Net-Zero: Assessing Procedures and Tools for Innovative Design of Urban Climate Governance in Europe
No full textopen access articleDespite the collective promise of integrating more open (broader-based, participatory) city-level governance into the global energy governance regime, little attention has been paid to the different impact logics and assumptions underpinning local procedural governance tools (PGTs) in circulation and the degree to which they address key good governance dimensions dominantly thought to be indicative of transformation. This review aims to fill this gap by mapping and analyzing key energy transition PGTs circulating across four climate action initiatives that mobilize and provide support to cities and local governments. A framework—REPAIR: Reflexivity, Enabling/Embedding, Participatory, Integrative, Adaptive, and Radicality—is proposed based on a synthesis of common governance innovation design features, and a representative sample of 25 PGTs are evaluated against these dimensions. The analysis reveals a need for (1) more differentiation and tailored capacity relating to governance monitoring, evaluating, and learning systems; (2) more attention to prioritization and design factors across different governance interventions in relation to local climate actions; and (3) more nuanced theories of change for operationalizing local power/coalition/mandate building (across different dimensions of governance). This article concludes that there are real gaps in how the collective advantages, opportunities, and promise of traveling “ideal types” of good governance will be fulfilled and outlines future research directions for informing more aligned governance innovation for low-carbon transitions in urban areas
Prediction of Urban Growth and Sustainability Challenges Based on LULC Change: Case Study of Two Himalayan Metropolitan Cities
No full textopen access article
Research England, grant number QR GCRF2020/21- IG.0070.02.19, titled “Capacity building for monitoring nature-based engineering projects for mountainous region incorporating spatial imaging”.Urbanization, characterized by population growth and socioeconomic development, is a major driving factor of land use land cover (LULC) change. A spatio-temporal understanding of land cover change is crucial, as it provides essential insights into the pattern of urban development. This study conducted a longitudinal analysis of LULC change in order to evaluate the tradeoffs of urban growth and sustainability challenges in the Himalayan region. Landsat time-series satellite imagery from 1988 to 2024 were analyzed for two major cities in Nepal—Kathmandu metropolitan city (KMC) and Pokhara metropolitan city (PMC). The LULC classification was conducted using a machine learning support vector machine (SVM) approach. For this study period, our analysis showed that KMC and PMC witnessed urban growth of over 400% and 250%, respectively. In the next step, LULC change and urban expansion patterns were predicted based on the urban development indicator using the Cellular Automata Markov chain (CA-Markov) model for the years 2040 and 2056. Based on the CA-Markov chain analysis, the projected expansion areas of the urban area for the two future years are 282.39 km2 and 337.37 km2 for Kathmandu, and 93.17 km2 and 114.15 km2 for PMC, respectively. The model was verified using several Kappa variables (K-location, K-standard, and K-no). Based on the LULC trends, the majority of urban expansion in both the study areas has occurred at the expense of prime farmlands, which raises grave concern over the sustainability of the food supply to feed an ever-increasing urban population. This haphazard urban sprawl poses a significant challenge for future planning and highlights the urgent need for effective strategies to ensure sustainable urban growth, especially in restoring local food supply to alleviate over-reliance on long-distance transport of agro-produce in high-altitude mountain regions. The alternative planning of sustainable urban growth could involve adequate consideration for urban farming and community gardening as an integral part of the urban fabric, both at the household and city infrastructure levels
Satisfaction with the Police in South Africa: Perspectives of University Students
No full textopen access articleThe present study explores satisfaction with the police among university students and factors that contribute to their perceptions. Citizens’ satisfaction with the police is an important element of public perceptions of the police. Existing scholarly literature has extensively examined this subject, albeit with a predominant emphasis on the broader population. As a result, there is a dearth of research on the perspectives of specific population segments, such as the youth more generally and university students in particular. Such a gap hinders the ability to make broad generalisations about research on satisfaction with the police and their applicability to those sub-groups of the population. This is particularly important as the youth, especially university students usually have frequent and acrimonious encounters and interactions with law enforcement agencies. Addressing this gap, the current study examines the determinants of university students' satisfaction with the police in South Africa through a cross-sectional survey. The results suggest that while participants highly value procedural fairness when assessing their satisfaction with the police, their primary concern is the efficacy of the police in reducing crime rates and ensuring community safety. The paper concludes by discussing the relevance of the findings for establishing and strengthening effective police-student relations in South Africa and beyond
Testing for contagion in international financial markets: to see more, go higher.
No full textThe file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.Traditional measures of financial contagion rely on correlation shifts, overlooking higher moments such as skewness and kurtosis. We examine contagion during two major financial crises, incorporating lower- and higher-moment measures. We analyze stock market returns from 22 major markets at different frequencies, offering a global perspective often missing in previous studies. Employing higher-order dependence measures, we demonstrate that conventional methods risk losing valuable information. Our contagion networks highlight how shocks travel outward. We find no systematic differences between developed and less developed economies’ vulnerability and stress the need for utilizing higher-order measures when assessing financial stability to avoid underestimating contagion risks
A Chaotic Image Encryption Scheme Using Novel Geometric Block Permutation and Dynamic Substitution
No full textIn this digital era, ensuring the security of digital data during transmission and storage is crucial. Digital data, particularly image data, needs to be protected against unauthorized access. To address this, this paper presents a novel image encryption scheme based on a confusion diffusion architecture . A novel geometric block permutation technique has been introduced, which effectively scrambles the pixels based on geometric shape extraction of pixels. The image is converted into four blocks, and pixels are extracted from these blocks using L-shape, U-shape, square-shape, and inverted U-shape patterns for each block, respectively. This robust extraction and permutation effectively disrupt the correlation within the image. Furthermore, the confusion module utilises bit-XOR and dynamic substitution techniques. For the bit-XOR operation, 2D Henon map has been utilised to generate a chaotic seed matrix, which is bit-XORed with the scrambled image. The resultant image then undergoes the dynamic substitution process to complete confusion phase. A statistical security analysis demonstrates the superior security of the proposed scheme with high uncertainty and unpredictability, achieving an entropy of 7.9974 and a correlation coefficient of 0.0014. These results validate the proposed scheme’s effectiveness in securing digital images