Search Results (617)

This paper introduces a novel physical layer authentication technique for Internet of Things (IoT) networks, leveraging channel state information (CSI) data from Wi-Fi signals to distinguish between authorised and unauthorised nodes and thereby enhancing security without compromising performance. The core novelty lies in its integrated framework, which employs non-negative matrix factorization (NMF) for efficient feature selection and a Gaussian mixture model (GMM) for identifying complex patterns within the CSI data specifically adapted to the dynamic nature of IoT networks. NMF is utilised to mitigate the high dimensionality and redundancy inherent in raw CSI metrics, reducing processing load, extracting salient features, alleviating overfitting risks, and exhibiting superior resilience to noise. Following NMF, the GMM component is used for data classification, capitalising on its probabilistic and soft clustering attributes to represent intricate distributions and handle heterogeneous CSI data characteristics. This integrated proposed methodology not only exploits the inherent nonlinear and probabilistic characteristics of CSI data but also upholds computational efficiency, making it highly suitable for implementation in resource-constrained IoT wireless networks. The model achieves exceptional classification proficiency, with an accuracy rate of 99.83 percent and a recall of 100 percent, which are crucial for cybersecurity and anomaly detection. Furthermore, the system is designed for efficiency and minimal resource consumption, exhibiting good computational efficiency, reduced training duration, and lower energy consumption compared with more complex, heavily exploited architectures for CSI data processing like CNN and CNN + LSTM, making it particularly suitable for resource-constrained IoT environments. Full article

Public-sector sustainability and climate reporting increasingly address environmental exposure, governance, and financial effects, yet existing frameworks do not adequately disclose preparedness for low-probability, high-impact systemic risks whose probabilities, timing, thresholds, and transmission channels remain deeply uncertain. This article develops a Public-Sector Resilience Reporting Standard (PSRRS) as a pre-standard architecture for government preparedness disclosure. The design has three bounded objectives: diagnose cross-framework disclosure gaps, translate these gaps into a theoretically grounded capability-to-disclosure architecture, and demonstrate its analytical use through an illustrative Florida application and two hazard-neutral stress tests. The documentary corpus includes international sustainability and public-sector reporting standards, ISO and UNDRR resilience and continuity instruments, three Florida resilience documents, and peer-reviewed literature on resilience governance, decision-making under deep uncertainty, critical infrastructure interdependency, catastrophic uncertainty, climate-risk disclosure, public finance, climate-risk pricing, local-government credit risk, investor attention, and ransomware service disruption. A structured interpretive coding protocol classifies each framework as explicit, partial, or not explicit across nine disclosure dimensions; a codebook appendix identifies the assessment criteria, the a priori and inductively refined dimensions, and the validation boundaries. Florida is not treated as a basis for statistical or jurisdictional generalization. Instead, it illustrates how a comparatively developed resilience architecture may disclose statutory continuity, critical-asset data, project ranking, and output metrics while leaving systemic dependencies, adaptive triggers, long-horizon fiscal exposure, residual service risk, distributional effects, and assurance mechanisms insufficiently visible in the reviewed reporting corpus. AMOC and case-grounded cyber-fiscal stress tests show how the PSRRS shifts reporting from hazard inventories and funded projects toward auditable evidence of institutional capacity, adaptive readiness, and public-value protection. The article specifies mandatory, recommended, and optional clauses, evidence requirements, indicator examples, a disclosure index, a sample report structure, and a three-tier pilot conformity model. The contribution is conceptual and operational, but not yet a validated formal standard; cross-jurisdictional piloting, inter-rater coding, cost testing, assurance testing, and stakeholder consultation are identified as the next stage of standardization. Full article

This paper investigates frequency manoeuvring as a method to improve the resilience of unmanned aerial vehicle (UAV) networks operating in contested electromagnetic environments. The study considers scenarios in which the network initially operates on a single channel and is then exposed to intentional jamming or unintentional interference affecting the primary channel, adjacent channels or a wider frequency range. Several response policies are compared, including no channel change, immediate switching after quality degradation is detected, delayed switching after a defined loss-of-connectivity interval, and periodic frequency hopping. In addition to channel switching, the analysis also considers changes in channel bandwidth, comparing narrower channels with lower throughput but potentially higher resistance to interference against wider channels with greater capacity but increased susceptibility to disruption. The evaluation includes the switching cost, which is modelled as temporary packet loss, additional delay and jitter during reconfiguration. Performance is assessed using the packet delivery ratio, latency, jitter, packet loss and communication continuity. The main objective is to identify the interference conditions under which frequency manoeuvring becomes operationally beneficial and to determine which policy offers the best trade-off between resilience and communication performance. In quantitative terms, immediate switching under environmental interference achieved a PDR of 0.961 and a mean latency of 123.6 ms compared with a PDR of 0.946 and a mean latency of 138.7 ms for fixed-channel operation. Manoeuvring gave a substantial 12.2-percentage-point PDR gain under jamming (periodic hopping: 0.780 vs. 0.658) and a 6.7-percentage-point gain under combined interference (0.674 vs. 0.607). These results indicate that manoeuvring is most worthwhile once interference is persistent and channel-focused rather than purely environmental. Full article

Understanding the interactions between vegetation dynamics and surface water availability is essential for assessing the resilience of tropical floodplain ecosystems under increasing hydroclimatic variability. This study analyzes the spatio-temporal dynamics of vegetation cover, surface water, and land use in Zambrano, a floodplain-dominated sector of the lower Magdalena River basin (Colombian Caribbean), over the period 1990–2025. Multi-temporal Landsat imagery was used to derive the Normalized Difference Vegetation Index (NDVI) and the Normalized Difference Water Index (NDWI), enabling the evaluation of seasonal and interannual ecohydrological variability under contrasting dry and rainy conditions. In addition, land-use classification was performed using a CORINE Land Cover methodology adapted for Colombia (CLC-C) to characterize the spatial organization of the landscape and its influence on vegetation–water interactions. Results show that vegetation dynamics are strongly controlled by hydroclimatic seasonality. Dense vegetation consistently expands during rainy periods, while dry seasons promote the expansion of open and sparse vegetation, reflecting seasonal vegetation stress rather than long-term degradation. NDWI patterns indicate that surface water and soil moisture are highly seasonal and spatially constrained, with open water largely confined to the Magdalena River channel and localized floodplain depressions. Extreme hydroclimatic events associated with the El Niño–Southern Oscillation (ENSO) produce abrupt but temporary changes in vegetation structure and surface moisture distribution. A strong inverse correlation between NDVI and NDWI reflects the contrasting spectral responses of vegetation and water surfaces resulting from the shared near-infrared (NIR) band in both indices. This spectral relationship is consistent with the observed seasonal variations in vegetation greenness and surface moisture across the floodplain. Land-use analysis reveals the progressive consolidation of the landscape, where the agropastoral matrix expanded from ~18,000 ha in 1990 to over 22,000 ha by 2025, driving a systematic reduction in natural and semi-natural forest structures. Forest conservation areas serve as critical ecological buffers, exhibiting lower seasonal variability in vegetation greenness. Overall, the results indicate that the Zambrano floodplain functions as a structurally stable yet highly responsive ecohydrological system, where vegetation dynamics and surface water availability are predominantly governed by interannual hydroclimatic pulses rather than long-term directional degradation. These findings demonstrate that while the structural matrix of the floodplain exhibits strong baseline resilience, its ecological functioning remains critically coupled with, and vulnerable to, the extreme phase shifts in ENSO cycles. Full article

Geopolitical uncertainty represents a growing source of systemic risk that reshapes international markets, disrupts cross-border operations, and challenges firms’ ability to sustain financial performance. This research examines the mechanisms through which geopolitical instability relates to firm financial outcomes in Southeast Asian economies by assessing the mediating roles of supply chain resilience, currency volatility, and foreign investment confidence. Based on a quantitative cross-sectional design, data were collected from 308 firms across Southeast Asian Economies and analyzed using partial least squares structural equation modeling (PLS-SEM). The findings indicate that geopolitical risks significantly influence financial performance, with the strongest effects transmitted through financial channels. Currency volatility and foreign investment confidence emerge as critical mediators, demonstrating that exchange rate instability and investor risk perceptions substantially shape firm performance under geopolitical pressure. While supply chain resilience enhances firms’ capacity to adapt to external disruptions, its direct contribution to financial performance remains insignificant. The model explains 66.7% of the variance in financial performance, reflecting strong explanatory capability. These findings extend existing knowledge by integrating financial, operational, and institutional mechanisms to clarify how geopolitical disruptions propagate into firm-level outcomes. The results underscore the importance of financial preparedness, institutional effectiveness, governance quality, and adaptive capabilities in managing geopolitical uncertainty. Full article

Artificial intelligence, digital payments and platform-based services are reshaping the operating conditions of Africa’s informal economy and micro-enterprise sector. While mobile money, digital marketplaces, app-mediated logistics and algorithmic scoring systems are commonly presented as instruments of financial inclusion and enterprise modernisation, their effects on informal traders remain uneven, conditional and under-governed. This systematic review synthesises recent peer-reviewed evidence on AI-mediated digitalisation pathways for informal and micro-enterprises in Africa, with particular attention to mobile money, platform payments, app-based logistics, digital credit, algorithmic management and platform governance. Following PRISMA-informed systematic review procedures, this review analyses 60 peer-reviewed, DOI-bearing articles published between April 2022 and June 2026 through a mechanism–outcome synthesis approach. The final corpus was selected through database searching, duplicate removal, title-and-abstract screening, full-text eligibility assessment, quality appraisal and mechanism–outcome coding. The findings show that digitalisation can expand market access, reduce cash-handling risks, create transaction histories, strengthen customer reach, improve operational continuity and support household resilience. However, the same digital infrastructures may also intensify livelihood vulnerability through opaque scoring, unexplained account freezes, fee shocks, exclusionary verification procedures, algorithmic ranking losses, data extraction and weak dispute-resolution mechanisms. The review therefore argues that informal enterprise digitalisation should not be understood only as a technology adoption issue, but as a socio-technical systems governance challenge. The article contributes a governance-and-risk framework linking local infrastructure, platform and payment design, AI (artificial intelligence) mediation, adoption conditions and livelihood outcomes. It further identifies minimum policy and design protections required for inclusive and resilient participation, including transparent fees, proportionate verification, human appeal channels, explainable restrictions, data-use consent, timely settlement and contingency mechanisms during digital outages or erroneous flags. The review concludes that sustainable digital inclusion for African informal micro-enterprises depends not merely on access to digital tools, but on the fairness, transparency, recoverability and accountability of the systems through which traders participate. Full article

Collaborative logistics strategies—both vertical supply-chain coordination and horizontal competitor cooperation—can improve resource utilization, service quality, and supply-chain resilience through cooperation among supply-chain actors. However, their implementation remains constrained by long-standing concerns regarding data transparency, confidentiality, and trust, while many blockchain-based proposals remain largely conceptual and lack empirical validation. This study addresses this gap by presenting the design, implementation, and evaluation of a multi-organizational Hyperledger Fabric network supporting both vertical and horizontal collaborative logistics interactions. The proposed network models independent factories, warehouses, and clients through separate organizations connected across dedicated collaboration channels and protected by Private Data Collections for confidential information exchange. The implementation was deployed on Kubernetes and evaluated through functional validation, privacy and governance tests, and Hyperledger Caliper performance benchmarks comprising more than 3000 transactions. Results demonstrate successful execution of collaborative logistics workflows, enforcement of access-control and confidentiality requirements, and quantification of performance under varying workloads. By providing a reproducible implementation and empirical evaluation, this paper contributes practical evidence on how blockchain technology can support collaborative logistics strategies beyond conceptual frameworks. Full article

The reconfiguration of global value chains has raised concerns about the resilience and upgrading of manufacturing supply chains. This study examines whether digital infrastructure improves manufacturing supply chain capabilities, using the 2016 “Information for the People” pilot city program as a quasi-natural experiment. Based on panel data from Chinese prefecture-level cities from 2006 to 2023, a difference-in-differences model is employed to identify the causal effect. The results show that digital infrastructure significantly enhances manufacturing supply chain capabilities, and this finding remains robust after multiple tests. Heterogeneity analysis indicates that the effect differs across China’s eight economic regions and strengthens with longer policy implementation, showing regional and cumulative characteristics. Mechanism analysis suggests that innovation-oriented talent inflow is an important transmission channel. Further analysis shows that financial development positively moderates the impact of digital infrastructure by improving cities’ capacity to absorb and allocate digital and innovation resources. These findings suggest that policymakers should shift from uniform digital infrastructure investment to region-specific strategies that integrate talent attraction, financial support, and supply chain modernization. Full article

Electric vehicle manufacturing firms face increasing supply chain vulnerability due to component shortages, technological interdependence, raw material volatility, and demand uncertainty. This study aims to examine whether digital transformation can be translated into a resilience-building capability and to identify the transmission channels. Using panel data from Chinese A-share listed electric vehicle manufacturing firms from 2014 to 2023, we employ a double machine learning framework to estimate the relationship between digital transformation and supply chain resilience while accounting for high-dimensional firm-level controls. The results show that digital transformation is positively associated with supply chain resilience. This finding remains robust across alternative sample-splitting ratios, different machine learning algorithms, alternative winsorization thresholds, and sample restrictions. It also holds after addressing potential endogeneity using instrumental variable estimation. Mechanism tests indicate that digital transformation contributes to resilience by promoting technological innovation and reducing managerial transaction costs. Heterogeneity analysis further shows that the effect is more pronounced among firms with stronger market positions, larger firms, and vehicle manufacturers. These findings suggest that digital transformation is not merely a tool for operational upgrading but also an important organizational capability for strengthening supply chain resilience in electric vehicle manufacturing. Full article

Against accelerating urban expansion, climate risks, and green transition, fortifying urban ecological resilience (UER) has become central to global urban sustainability. However, there is as yet no systematic evidence to suggest how the National Innovative City Pilot Policy (NICPP) promotes green technology innovation (GTI) and strengthens UER. To address this gap, this paper builds upon the traditional resistance–adaptability–resilience (RAR) paradigm and its extension, the driving force–resistance–adaptability–resilience (DRAR) framework to formulate a comprehensive driving force–pressure–resistance–adaptability–resilience (DPRAR) assessment system. Moreover, this paper investigates a dataset of 271 cities in China spanning the period from 2006 to 2023. By treating the NICPP as a quasi-natural experiment, this paper integrates an entropy balancing technique into a staggered difference–in–differences (DID) model to identify its effect on UER. The results are outlined below. (1) From 2006 to 2023, UER across Chinese municipalities generally increased, though spatial imbalances persisted. (2) The NICPP enhanced urban UER, with effects characterized by time-lagged and cumulative patterns. (3) Both the quantity and quality structure of urban GTI served as channels through which the NICPP affected UER. (4) The NICPP effects are strongest in the central region, followed by those in the western and eastern regions, as well as in resource-dependent cities and cities with stricter environmental regulation. This research provides novel empirical perspectives linking innovation-driven development, GTI, and UER, with implications for NICPP optimization and UER enhancement in China. Full article

Low-light image enhancement (LLIE) is a fundamental task in computer vision, required for restoring luminance, contrast, and structural fidelity in images captured under suboptimal lighting environments. This paper introduces an optimization-driven, scene-adaptive LLIE framework, designated as $O{M}_{\mathrm{I}\mathrm{D}\mathrm{C}\mathrm{P}}^{\mathrm{G}\mathrm{C}\mathrm{G}\mathrm{L}}$, which exploits the optical duality between low-light inversion and atmospheric scattering. The proposed methodology transforms low-light inputs into quasi-haze representations through an optical inversion process, followed by structural restoration using an Improved Dark Channel Prior ($M_{\mathrm{I}\mathrm{D}\mathrm{C}\mathrm{P}}$) baseline. To refine the restored output, a Gamma Correction with Global Limits (GCGL) module is integrated as a boundary constraint to mitigate localized over-exposure and preserve chromatic consistency. A core novelty of this framework lies in the deployment of metaheuristic optimization algorithms (MOAs)—specifically the Gray Wolf Optimizer (GWO), Harris Hawks Optimization (HHO), and Marine Predators Algorithm (MPA)—to autonomously resolve optimal, image-specific parameter configurations. This search paradigm is guided by perception-driven fitness functions, namely the Patch-based Contrast Quality Index (PCQI) or the Blind/Referenceless Image Spatial Quality Evaluator (BRISQUE). Quantitative and qualitative evaluations across a comprehensive pool of 1092 benchmark images demonstrate that the proposed framework exhibits robust statistical resilience and cross-dataset generalization compared to four state-of-the-art deep learning methods. While data-driven deep learning architectures retain localized superiority under the extreme degradation boundaries of the DARK FACE dataset, the proposed physics-inspired optimization framework achieves the leading overall cross-dataset aggregate ranking ($\overline{R}=2.467$) across diverse evaluation environments due to its per-image dynamic solution space mapping. Full article

Although rural public cultural spaces in China have expanded rapidly, many struggle to maintain stable and sustained public participation. Taking Sanchalu Village in Wuhan as a case, this study examines how multi-actor interactions transform fragmented and short-term participation into a resilient participatory structure. Using a constructivist grounded theory approach, the study analyzed semi-structured interviews with 13 government officials, village cadres, enterprise representatives, and villagers, supplemented by participant observation and documentary materials. The findings identify an adaptive linkage process in which external resource embedding activates participation, village-level organizations promote the institutionalization of participation through incentive mechanisms and participation channels, internal and external resources are integrated through trust-based reciprocity, and multi-actor collaboration stabilizes governance arrangements. Accordingly, participation resilience develops through sustained participation, organizational mediation, and institutional safeguards rather than through infrastructure provision alone. This study clarifies how participation resilience supports the social sustainability of rural public cultural spaces and offers practical guidance for developing demand-responsive, locally embedded, and institutionally sustained participation mechanisms. Full article

Digital finance is reshaping financial intermediation through platform-based credit, stablecoin-based payment and settlement arrangements, and a rapidly deepening reliance on critical third-party technology providers. Existing international frameworks identify many of these vulnerabilities, but macroprudential authorities still lack a traceable operational bridge from FinTech activities to systemic-risk channels, measurable indicators, stress-test assumptions and staged policy escalation. This article proposes the FinTech Macroprudential Integration Framework (FMIF) as an evidence-mapped operationalisation layer for existing macroprudential regimes. The FMIF does not claim to replace the frameworks issued by the FSB, BIS, IMF, BCBS, the EU or cyber-resilience authorities; instead, it translates their risk taxonomies and policy insights into a structured workflow linking activity perimeter, dependency registry, indicator formulas, modular stress tests and governance interfaces. The framework is developed for three activity clusters: platform credit and bank–FinTech partnerships; stablecoin-based payment and settlement; and critical third-party technology dependencies. These clusters are mapped to three channels: liquidity/run dynamics, interconnectedness and market spillovers, and operational concentration/correlated disruption. The article contributes by clarifying the research gap, disclosing the evidence-mapping procedure and source-level coding, classifying evidence quality, specifying indicator formulas and calibration principles, adding a stablecoin-run illustrative application, and discussing legal and institutional feasibility. The FMIF should be understood as a decision-support and decision-preparedness framework rather than as a fully validated decision-ready model. Empirical validation, jurisdiction-specific thresholds and legal triggers remain necessary next steps. Full article

With the acceleration of global economic integration and the continuous rise of external uncertainties, the resilience and security of industrial and supply chains have become core benchmarks for measuring an economy’s risk resistance and sustainable development capacity, which is crucial to the stable operation of the modern economic system. Based on panel data covering 279 prefecture-level and above cities in China from 2003 to 2023, this paper takes the Pilot Program for Integrating Science, Technology and Finance as a quasi-natural experiment, and adopts a multi-period DID model to empirically examine the correlation between sci-tech finance policies and urban industrial chain resilience, as well as explore its potential transmission pathways. The results show that the pilot policy significantly improves urban industrial chain resilience. Financial deepening level, high-tech application level, and urban informatization level may serve as potential transmission channels through which the policy functions. Further heterogeneity analysis indicates that the policy effect varies markedly across cities in terms of location, scale, urban resource endowments, and industrial foundation. This study enriches relevant research on sci-tech finance policy effects and industrial chain resilience and provides theoretical basis and practical reference for optimizing sci-tech finance system design and consolidating industrial chain security. Full article

Fiscal shocks in post-land-finance China are weakening the funding basis of capital-intensive metro public-private partnership (PPP) projects, but the system-level mechanism through which public fiscal stress becomes subcontractor-level financial viability pressure remains underexplained. This study examines a section-level metro PPP project ecosystem in a sub-provincial Chinese city to trace this transmission mechanism and its financial implications. The analysis combines de-identified audit evidence and interviews with a scenario-based structural NPV model and 800,000 model-generated Monte Carlo realizations under calibrated institutional scenarios. The evidence indicates that quasi-bureaucratic SPV internal capital-market arrangements convert fiscal shortfalls into vertical and horizontal cross-subsidization practices, preserving short-term project continuity while shifting cash-flow pressure downstream. This condition is defined as a strategic resilience trap: practices that preserve short-term project continuity while potentially eroding the project ecosystem’s long-term adaptive capacity. Under calibrated assumptions, improving the contract-payment channel reduces model-generated losses by approximately 4%, suggesting that payment punctuality addresses only one part of the wider internal capital-market mechanism. Full article