Search Results (12,184)

This research focuses on enhancing cooperative localization for heterogeneous mobile robots composed of a quadcopter and an unmanned ground vehicle. The study employs sensor fusion techniques, particularly the Extended Kalman Filter, to fuse data from various sensors, including GPSs, IMUs, and cameras. By integrating these sensors and optimizing fusion strategies, the research aims to improve the precision and reliability of cooperative localization in complex and dynamic environments. The primary objective is to develop a practical framework for cooperative localization that addresses the challenges posed by the differences in mobility and sensing capabilities among heterogeneous robots. Sensor fusion is used to compensate for the limitations of individual sensors, providing more accurate and robust localization results. Moreover, a comparative analysis of different sensor combinations and fusion strategies helps to identify the optimal configuration for each robot. This research focuses on the improvement of cooperative localization, path planning, and collaborative tasks for heterogeneous robots. The findings have broad applications in fields such as autonomous transportation, agricultural operation, and disaster response, where the cooperation of diverse robotic platforms is crucial for mission success. Full article

This essay examines two hybrid poetic texts that emerged from a period of feminist activism in U.S. and global poetry communities from 2014 to 2017: the collaboratively, anonymously authored “No Manifesto” (2015) and the radically revised second edition of the book of poetry and visual art YOU DA ONE by Jennif(f)er Tamayo. “No Manifesto” and YOU DA ONE embrace the hybrid tactics of collectivity, incongruity, and nonresolution as ways of protesting sexism and sexual violence in poetry communities. Synthesizing theories of hybridity from poetry criticism as well as immigrant and borderlands studies, the essay defines hybridity as a literary representation of cultural positions forcefully imposed upon subjects. Born out of the domination of sexual and state violence, hybridity marks the wound that remakes the subject, who develops strategies for resistance. By refusing to play by the rules of poetic or social discourse—the logics of domination that would have them be singular, cohesive, and compliant—Tamayo and the authors of “No Manifesto” insist on alternative ways of performing activism, composing literature, and entering the public sphere. These socially engaged, hybrid poetic texts demonstrate the power of the collective to disrupt the social and literary status quo. Full article

This study examines the added value of territorial cooperation within the LEADER approach, a key pillar of the EU’s rural development policy. Both interterritorial and transnational cooperation projects empower Local Action Groups (LAGs) to tackle common challenges through innovative and community-driven strategies. Drawing on over 3000 projects since 1994, LEADER cooperation has proven its ability to deliver tangible results—such as joint publications, pilot projects, and shared digital platforms—alongside intangible benefits like knowledge exchange, improved governance, and stronger social capital. By facilitating experiential learning and inter-organizational collaboration, cooperation enables stakeholders to work across territorial boundaries and build networks that respond to both national and transnational development issues. The interaction among diverse actors often fosters innovative responses to local and regional problems. Using a mixed-methods approach, including case studies of Italian LAGs, this research analyses the dynamics, challenges, and impacts of cooperation, with a focus on learning processes, capacity building, and long-term sustainability. Therefore, this study focuses not only on project outcomes but also on the processes and learning dynamics that generate added value through cooperation. The findings highlight how territorial cooperation promotes inclusivity, fosters cross-border dialogue, and supports the development of context-specific solutions, ultimately enhancing rural resilience and innovation. In conclusion, LEADER cooperation contributes to a more effective, participatory, and sustainable model of rural development, offering valuable insights for the broader EU cohesion policy. Full article

The terminal maneuvering area (TMA) serves as a critical transition zone between upper enroute airways and airports, representing one of the most complex regions for managing high volumes of arrival and departure traffic. This paper presents the multi-route TMA scheduling problem as an optimization challenge aimed at optimizing TMA interventions, such as rerouting, speed control, time-based metering, dynamic minimum time separation, and holding procedures; the objective function minimizes schedule deviations and the accumulated holding time. Furthermore, the problem is formulated as a mixed-integer linear program (MILP) to facilitate finding solutions. A rolling horizon control (RHC) dynamic optimization framework is also introduced to decompose the large-scale problem into manageable subproblems for iterative resolution. To demonstrate the applicability and effectiveness of the proposed scheduling models, a hub airport—Chengdu Tianfu International Airport (ICAO code: ZUTF) in the Cheng-Yu Metroplex—is selected for validation. Numerical analyses confirm the superiority of the proposed models, which are expected to reduce aircraft delays, shorten airborne and holding times, and improve airspace resource utilization. This study provides intelligent decision support and engineering design ideas for the macroscopic-level collaborative optimization framework of the Integrated Arrival–Departure and Surface (IADS) system. Full article

Peste des petits ruminants is a highly contagious transboundary viral disease that poses a serious threat to small ruminant populations worldwide. In 2024, seven outbreaks of PPR were recorded in sheep flocks from Timiș County, marking the second confirmed incursions of peste des petits ruminants virus (PPRV) in Romania. This study aimed to document the clinical presentation, pathological findings, and diagnostic confirmation with these field outbreaks. Comprehensive field investigations were carried out between July and September 2024, including clinical examinations, post mortem analysis, serological screening, and molecular detection using reverse transcription polymerase chain reaction (RT-PCR). A total of 13,203 sheep were evaluated, with an overall mortality rate of 12.77%. Characteristic clinical signs included mucopurulent nasal discharge, oral erosions, respiratory distress, and diarrhea. Gross lesions observed during necropsy included hemorrhagic bronchopneumonia, bile-stained liver, catarrhal enteritis, and mucosal hemorrhages. Serological testing revealed flock-level seroprevalence rates ranging from 46.7% to 80.0%, with higher rates observed in older animals. RT-PCR confirmed PPRV infection in all affected flocks. Our findings provide strong evidence of virulent PPRV circulation in an area where the virus had not been reported before. The results highlight an urgent need to strengthen surveillance systems, enhance diagnostic capacity, and foster cross-border collaboration. These field-based insights can contribute to both national and international efforts aimed at controlling and ultimately eradicating the disease. Full article

Skin cancer is one of the most prevalent forms of cancer worldwide, and early and accurate diagnosis critically impacts patient outcomes. Given the sensitive nature of medical data and its fragmented distribution across institutions (data silos), privacy-preserving collaborative learning is essential to enable knowledge-sharing without compromising patient confidentiality. While federated learning (FL) offers a promising solution, existing methods struggle with heterogeneous and missing modalities across institutions, which reduce the diagnostic accuracy. To address these challenges, we propose an effective and flexible Personalized Multimodal Federated Learning framework (PMM-FL), which enables efficient cross-client knowledge transfer while maintaining personalized performance under heterogeneous and incomplete modality conditions. Our study contains three key contributions: (1) A hierarchical aggregation strategy that decouples multi-module aggregation from local deployment via global modular-separated aggregation and local client fine-tuning. Unlike conventional FL (which synchronizes all parameters in each round), our method adopts a frequency-adaptive synchronization mechanism, updating parameters based on their stability and functional roles. (2) A multimodal fusion approach based on multitask learning, integrating learnable modality imputation and attention-based feature fusion to handle missing modalities. (3) A custom dataset combining multi-year International Skin Imaging Collaboration(ISIC) challenge data (2018–2024) to ensure comprehensive coverage of diverse skin cancer types. We evaluate PMM-FL through diverse experiment settings, demonstrating its effectiveness in heterogeneous and incomplete modality federated learning settings, achieving 92.32% diagnostic accuracy with only a 2% drop in accuracy under 30% modality missingness, with a 32.9% communication overhead decline compared with baseline FL methods. Full article

To address the challenges of complex low-altitude flight environments for UAVs, where numerous obstacles often lead to GPS signal obstruction and multipath effects, this study proposes an integrated inertial navigation and GPS positioning approach for coordinated cross-path planning in drone swarms. The methodology involves the following: (1) discretizing continuous 3D airspace into grid cells using occupancy grid mapping to construct an environmental model; (2) analyzing dynamic flight characteristics through attitude angle variations in a 3D Cartesian coordinate system; and (3) implementing collaborative state updates and global positioning through fused inertial–GPS navigation. By incorporating Cramér–Rao lower bound optimization, the system achieves effective cross-path planning for drone formations. Experimental results demonstrate a 98.35% mission success rate with inter-drone navigation time differences maintained below 0.5 s, confirming the method’s effectiveness in enabling synchronized swarm operations while maintaining safe distances during cooperative monitoring and low-altitude flight missions. This approach demonstrates significant advantages in coordinated cross-path planning for UAV clusters. Full article

This study examines the integration and sustainability of solar energy technologies as a tool for rural electrification in Ghana, using the Lofetsume community as a case study. Persistent electricity access deficits in rural areas, coupled with unreliable grid systems and high energy costs, underscore the need for alternative energy solutions. Through semi-structured interviews and surveys, the study explores community perspectives and expert views on the viability of solar energy in rural Ghana. Findings reveal strong grassroots support for solar energy due to its reliability and environmental benefits, despite barriers such as high upfront installation costs and maintenance challenges. The study recommends multi-stakeholder partnerships, innovative financing models, and capacity-building initiatives to enhance solar energy adoption. By prioritizing solar energy technologies, the government, private sector, and local communities can collaborate to develop sustainable and affordable electrification solutions, ultimately improving living standards in remote areas and contributing to Ghana’s broader energy sustainability goals. Full article

The evolution of 3GPP non-terrestrial networks (NTNs) is enabling new avenues for broadband connectivity via satellite, especially within the scope of 5G. The parallel rise in satellite mega-constellations has further fueled efforts toward ubiquitous global Internet access. This convergence has fostered collaboration between mobile network operators and satellite providers, allowing the former to leverage mature space infrastructure and the latter to integrate with terrestrial mobile standards. However, integrating these technologies presents significant architectural challenges. This study investigates 5G NTN architectures using satellite mega-constellations, focusing on transparent architectures where Starlink is employed to relay the backhaul, midhaul, and new radio (NR) links. The performance of these architectures is assessed through a testbed utilizing OpenAirInterface (OAI) and Open5GS, which collects key user-experience metrics such as round-trip time (RTT) and jitter when pinging the User Plane Function (UPF) in the 5G core (5GC). Results show that backhaul and midhaul relays maintain delays of 50–60 ms, while NR relays incur delays exceeding one second due to traffic overload introduced by the RFSimulator tool, which is indispensable to transmit the NR signal over Starlink. These findings suggest that while transparent architectures provide valuable insights and utility, regenerative architectures are essential for addressing current time issues and fully realizing the capabilities of space-based broadband services. Full article

In rice detection tasks, accurate identification of leaf streaks, pest and disease distribution, and spikelet hierarchies relies on high-quality images to distinguish between texture and hierarchy. However, existing images often suffer from texture blurring and contour shifting due to equipment and environment limitations, which affects the detection performance. In view of the fact that pests and diseases affect the whole situation and tiny details are mostly localized, we propose a rice image reconstruction method based on an adaptive two-branch heterogeneous structure. The method consists of a low-frequency branch (LFB) that recovers global features using orientation-aware extended receptive fields to capture streaky global features, such as pests and diseases, and a high-frequency branch (HFB) that enhances detail edges through an adaptive enhancement mechanism to boost the clarity of local detail regions. By introducing the dynamic weight fusion mechanism (CSDW) and lightweight gating network (LFFN), the problem of the unbalanced fusion of frequency information for rice images in traditional methods is solved. Experiments on the 4× downsampled rice test set demonstrate that the proposed method achieves a 62% reduction in parameters compared to EDSR, 41% lower computational cost (30 G) than MambaIR-light, and an average PSNR improvement of 0.68% over other methods in the study while balancing memory usage (227 M) and inference speed. In downstream task validation, rice panicle maturity detection achieves a 61.5% increase in mAP50 (0.480 → 0.775) compared to interpolation methods, and leaf pest detection shows a 2.7% improvement in average mAP50 (0.949 → 0.975). This research provides an effective solution for lightweight rice image enhancement, with its dual-branch collaborative mechanism and dynamic fusion strategy establishing a new paradigm in agricultural rice image processing. Full article

The number of publications in the scientific literature dealing with geomorphological mapping has increased over the last two decades. Although geomorphological maps are utilised in various contexts, such as hazard assessment, archaeology, and tourism, there is a noticeable lack of interaction between geomorphological products and the social sciences. This study aims to provide a qualitative assessment of the literature on geomorphological maps published in the 2000s with the intent of identifying the purpose of mapping and its field of application. Additionally, a comparative analysis was conducted of the articles relating to both geomorphological maps and social issues to identify the tools that facilitate this interdisciplinary collaboration. The results facilitated the identification of the primary fields of interest for map production, showing that only a limited number of articles employed geomorphological maps for social purposes, for instance, enhancing risk awareness and educating the population about natural hazards. Moreover, the analysis reveals that only a limited number of geomorphological maps are intended to be accessible to people without a high degree of education in earth sciences. In particular, this study highlights a lack of attention to non-specialist users who may struggle to understand the information contained in geomorphological maps. This issue limits the dissemination of geomorphological maps, which are, however, vital for territorial planning and practical purposes. The analyses prompted the authors to consider novel applications of research tools to enhance the dissemination of geomorphological maps, even among non-specialist users. Full article

Developing multicultural leadership in youth is crucial for fostering social harmony, emphasizing cross-cultural communication, adaptability, creative problem solving, and ethical leadership, particularly in Thailand’s three southern border provinces. This study aimed to analyze the confirmatory factors and assess the validity of the measurement model for multicultural leadership among youth in Thailand’s three southern border provinces. The study sample comprised 640 participants, and the data were analyzed using second-order confirmatory factor analysis. The findings revealed that multicultural leadership among youth in the region consists of the following six key components: (1) awareness and acceptance of cultural diversity, (2) intercultural communication skills, (3) flexibility and adaptability in multicultural contexts, (4) creative problem solving in a multicultural context, (5) building intercultural collaboration networks, and (6) developing culturally relevant morality and ethics. The measurement model demonstrated a good fit with the empirical data. Considering the Chi-square value of 411.81, p-value of 0.07, the relative Chi-square (χ²/df) was 1.11, the Goodness-of-Fitness Index (GFI) was 0.96, the Adjusted Goodness-of-Fitness Index (AGFI) was 0.94, and the Root Mean Square Residuals Index (SRMR) was 0.03. These findings provide valuable insights for formulating effective policies and concrete strategies to enhance and develop multicultural leadership among youth in diverse sociocultural contexts. Full article

In recent decades, university dormitories have gradually evolved from traditional residential spaces into educationally meaningful venues that support informal learning. However, limited research has explored how supportive environmental factors within dormitories influence students’ informal learning experiences. This study aims to evaluate key environmental factors that affect students’ satisfaction with informal learning in dormitory settings. Based on a comprehensive literature review, two types of informal learning behaviors—individual and collaborative—were defined, and a multi-dimensional evaluation framework comprising five categories and 26 environmental indicators was established. Field observations and structured questionnaires were employed to assess students’ satisfaction with each environmental factor and their overall informal learning experiences. Quantitative analyses were conducted to examine the relationships between environmental conditions and learning satisfaction. Results show that all five-factor categories—spatial designs, natural environments, physical settings, social aspects, and resources—positively influence informal learning, with resources being the most impactful. While environmental influences on individual and collaborative learning exhibit minor differences, the overall patterns are consistent. Compared to other informal learning spaces on campus, dormitory users place greater emphasis on spatial controllability. This study further demonstrates the cognitive and emotional value of dormitory environments and proposes targeted directions for optimizing them as informal learning spaces. Full article

The integration of water resources, water environment, and water ecology (hereinafter “three-water”) is essential not only for addressing the current water crisis but also for achieving sustainable development. Chaohu Lake is an important water resource and ecological barrier in the middle and lower reaches of the Yangtze River, undertaking such functions as agricultural irrigation, urban water supply, and flood control and storage. Studying the performance of “three-water” in the Chaohu Lake Basin will help to understand the pollution mechanism and governance dilemma in the lake basin. It also provides practical experience and policy references for the ecological protection and high-quality development of the Yangtze River Basin. We used the DPSIR-TOPSIS model to analyze the performance of the river–lake system in the Chaohu Lake Basin and employed an obstacle model to identify factors influencing “three-water.” The results indicated that overall governance and performance of the “three-water” in the Chaohu Lake Basin exhibited an upward trend from 2011 to 2022. Specifically, the obstacle degree of driving force decreased by 19.6%, suggesting that economic development enhanced governance efforts. Conversely, the obstacle degree of pressure increased by 34.4%, indicating continued environmental stress. The obstacle degree of state fluctuated, showing a decrease of 13.2% followed by an increase of 3.8%, demonstrating variability in the effectiveness of water resource, environmental, and ecological management. Additionally, the obstacle degree of impact declined by 12.8%, implying the reduced efficacy of governmental measures in later stages. Response barriers decreased by 5.8%. Variations in the obstacle degree of response reflected differences in response capacities. Spatially, counties and districts at the origins of major rivers and their lake outlets showed lower performance levels in “three-water” management compared to other regions in the basin. Notably, Wuwei City and Feidong County exhibited better governance performance, while Feixi County and Chaohu City showed lower performance levels. Despite significant progress in water resource management, environmental improvement, and ecological restoration, further policy support and targeted countermeasures remain necessary. Counties and districts should pursue coordinated development, leverage the radiative influence of high-performing areas, deepen regional collaboration, and optimize, governance strategies to promote sustainable development. Full article

Secure Digital Evidence Management Systems (DEMSs) ae crucial for law enforcement agencies, because traditional systems are prone to tampering and unauthorised access. Blockchain technology, particularly private blockchains, offers a solution by providing a centralised and tamper-proof system. This study proposes a private blockchain using Proof of Work (PoW) to securely manage digital evidence. Miners are assigned specific nonce ranges to accelerate the mining process, called collaborative mining, to enhance the scalability challenges in DEMSs. Transaction data includes digital evidence to generate a Non-Fungible Token (NFT). Miners use NFTs to solve the puzzle according to the assigned difficulty level d, so as to generate a hash using SHA-256 and add it to the ledger. Users can verify the integrity and authenticity of records by re-generating the hash and comparing it with the one stored in the ledger. Our results show that the data was verified with 100% precision. The mining time was $2.5$ s, and the nonce iterations were as high as $80\times {10}^3$ for $d=5$. This approach improves the scalability and integrity of digital evidence management by reducing the overall mining time. Full article