Search Results (1,221)

Trajectory planning is a key task in unmanned aerial vehicle navigation systems. Although trajectory planning in the presence of obstacles is a well-understood problem, unknown and dynamic environments still present significant challenges. In this paper, we present a trajectory planning method for unknown and dynamic environments that explicitly incorporates the uncertainty about the environment. Assuming that the position of obstacles and their instantaneous movement are available, our method represents the environment uncertainty as a dynamic map that indicates the probability that a region might be occupied by an obstacle in the future. The proposed method first divides the free space into non-overlapping tetrahedral partitions using Delaunay triangulation. Then, a topo-graph that describes the topology of the free space and incorporates the uncertainty of the environment is created. Using this topo-graph, an initial path and a safe flight corridor are obtained. The initial safe flight corridor provides a sequence of control points that we use to optimize clamped B-spline trajectories by formulating a quadratic programming problem with safety and smoothness constraints. Using computer simulations, we show that our algorithm can successfully find a collision-free and uncertainty-aware trajectory in an unknown and dynamic environment. Furthermore, our method can reduce the computational burden caused by moving obstacles during trajectory replanning. Full article

Extracting building outlines from 3D models poses significant challenges stemming from the intricate diversity of structures and the complexity of urban scenes. Current techniques heavily rely on human expertise and involve repetitive, labor-intensive manual operations. To address these limitations, this paper presents an innovative automatic technique for accurately extracting building footprints, particularly those with gable and hip roofs, directly from 3D data. Our methodology encompasses several key steps: firstly, we construct a triangulated irregular network (TIN) to capture the intricate geometry of the buildings. Subsequently, we employ 2D indexing and counting grids for efficient data processing and utilize a sophisticated connected component labeling algorithm to precisely identify the extents of the roofs. A single seed point is manually specified to initiate the process, from which we select the triangular facets representing the outer walls of the buildings. Utilizing the projection histogram method, these facets are grouped and processed to extract regular building footprints. Extensive experiments conducted on datasets from Nanjing and Wuhan demonstrate the remarkable accuracy of our approach. With mean intersection over union (mIOU) values of 99.2% and 99.4%, respectively, and F1 scores of 94.3% and 96.7%, our method proves to be both effective and robust in mapping building footprints from 3D real-scene data. This work represents a significant advancement in automating the extraction of building footprints from complex 3D scenes, with potential applications in urban planning, disaster response, and environmental monitoring. Full article

A graph, $G=(V,E)$, is edge odd graceful if it possesses edge odd graceful labeling. This labeling is defined as a bijection $g:E\left(G\right)\to \{1,3,\dots ,2m-1\}$, from which an injective transformation is derived, $g^{*}:V\left(G\right)\to \{1,2,3,\dots ,2m-1\}$, from the rule that the image of $u\in V\left(G\right)$ under $g^{*}$ is ${\sum }_{uv\in E\left(G\right)}g\left(uv\right)\mathrm{mod}\left(2m\right)$. The main objective of this manuscript is to introduce new classes of planar graphs, namely water wheel graphs, $W{W}_n$; triangulated water wheel graphs, $T{W}_n$; closed water wheel graphs, $C{W}_n$; and closed triangulated water wheel graphs, $C{T}_n$. Furthermore, we specify conditions for these graphs to allow for edge odd graceful labelings. Full article

Since the early 21st century, wildlands have witnessed an effusion of wildfires, with climate and social changes resulting in unanticipated wildfire activity and impact. For forest fires to be prevented and suppressed effectively, forest firefighting forces have adopted a specific administrative system for organizing and managing the fighting force. Under the administrative system, a debate on desired “leadership and management qualities” arises, and hence, this study sought to identify the leadership and management traits that should distinguish individuals in the forest fire incident command system (FFICS) applied by the Department of Forests (Cyprus). The research subject was addressed using mixed method research, employing quantitative and qualitative data. Both datasets were used to distinguish the purposes of the applied triangulation, enabling the examination of differentiation between the trends/positions recorded in terms of the object of study. These findings point to ideal forms of transformational leadership and neoclassical management. The outcomes suggest that at the individual level, the leaders of each of the operating structures should develop leadership qualities related to emotional intelligence, empathy, judgment, critical thinking, and especially self-awareness of strengths and weaknesses. At the stage of pre-suppression, a democratic leadership style (or guiding style) is supported, while during the operational progress stage of the FFICS, a “hybrid” leadership style is suggested, borrowing elements from the democratic and authoritarian (or managerial) leadership styles. The administrative skills of FFICS leaders should include the moral and psychological rewards of subordinates, job satisfaction and recognition, and two-way communication. The current study illustrates the need for divergent leadership and management traits and styles among the different hierarchical structures of the FFICS. Full article

The paper describes a planetary laser interferometric seismoacoustic observatory consisting of six stationary unequal arm laser strainmeters. Based on the triangulation method, the fundamentals of direction finding of various infrasound disturbances at any planetary distance have been developed. The authors show that in addition to determining locations of the occurrence of the recorded disturbance, using data from spatially separated laser strainmeters, it is possible to determine the nature of these signals’ divergence and, also, the loss of their energy in the propagation medium. The creation of the planetary laser interferometric seismoacoustic observatory, consisting of five stationary single-coordinate laser strainmeters and one two-coordinate laser strainmeter, united into a single measuring network with an accurate time clock TRIMBLE 5700 that is capable of recording displacements on their bases with an accuracy of 10 pm in the frequency range from 0 (conventionally) to 1000 Hz and two auxiliary laser strainmeters, will allow us to determine, at any planetary distance, the primary source of deformation infrasound disturbances with primary amplitudes from 100 nm. Full article

Background/Objectives: Robot-assisted radical prostatectomy (RARP) for the treatment of prostate cancer (PCa) has been standardized over the last 20 years. At our institution, only n = 3 rob arms are used for RARP. In addition, n = 2, 12 mm lap trocars are placed for the bedside assistant symmetrically at the midclavicular lines, which allows for direct pelvic triangulation and greater involvement of the assisting surgeon. The aim of our study was to compare surgical and perioperative outcomes of RARP performed using our alternative trocar placement with no fourth robotic arm in the subgroups of experienced attending surgeons and post-graduate residents as bedside assistants. Residents’ satisfaction was also explored. Methods: RARPs performed within the urology residency program between 2019 and 2024 were retrospectively analyzed. Only rob procedures performed using our 3+2 trocars configuration were included. Intra- and postoperative outcomes, as well as long-term functional outcomes including continence recovery and potency, were assessed, stratified by the level of expertise of the bedside assistant, i.e., an experienced attending or post-graduate Year I–III resident. Satisfaction of residents assigned to the two groups during their robotic rotation was evaluated considering three domains with a score from 1 to 10: insight into surgical procedure, confidence level, and gratification level. Results: Out of n = 281 RARP procedures, the bedside assistant was an attending in 104 cases and a resident in 177. Operative time was found to be slightly longer in cases where the second operator was a resident (attendings vs. residents: 134 ± 40 vs. 152 ± 24; p < 0.001). Postoperative hospitalization time was longer in patients in the resident group (attendings vs. residents: 3.9 ± 1.6 vs. 4.3 ± 1 days; p = 0.025). However, cases where the second operator was a resident had a lower rate of positive surgical margins, with rates of 19.7% in the resident and 43.3% in the attending surgeon cohorts (OR = 0.32; 95% CI 0.18–0.55). This difference remained significant in multivariate analysis. There was no significant difference in postoperative blood transfusion rates (attendings vs. residents: 1.9% vs. 1.2%; p = 0.6). Similarly, long-term functional outcomes in terms of erectile dysfunction and urinary incontinence rates mostly overlapped between groups. The mean score in all three domains evaluating residents’ satisfaction was significantly higher when residents actively participated in the surgical procedure as bedside assistants (p = 0.02, p = 0.004, and p < 0.001, respectively, for insights into surgical procedure, confidence level, and gratification level). Conclusions: These findings provide insight into how an alternative port positioning during RARP could improve the involvement of the bedside assistant, particularly residents, without compromising perioperative outcomes or surgical safety. Full article

To effectively monitor the nonlinear wear variation of tools during the processing of titanium alloys, this study proposes a hybrid deep neural network fault diagnosis model that integrates the triangulation topology aggregation optimizer (TTAO), convolutional neural network (CNN), bidirectional long short-term memory network (BiLSTM), and attention mechanism (AM). Firstly, vibration signals from the machine tool spindle are acquired and subjected to the wavelet packet transform (WPT) to extract multi-frequency band energy features as model inputs. Then, the CNN and BiLSTM modules capture the features and temporal relationships of the input signals. Finally, introduction of the AM, combined with the TTAO algorithm, automatically extracts deep features, overcoming issues such as local optima and slow convergence in traditional neural networks, thereby enhancing the accuracy and efficiency of tool wear state recognition. The experimental results demonstrate that the proposed model achieves an average accuracy rate of 98.649% in predicting tool wear states, outperforming traditional backpropagation (BP) networks and standard CNN models. Full article

Despite various opportunities, urban development projects have been causing significant challenges to the preservation and conservation of historic cultural heritage. In particular, an increasing number of World Heritage (WH) properties are impacted by the direct and indirect effects of development projects, reflecting the existing uprising conflict. Grasping the challenge, Heritage Impact Assessment (HIA) has been developed as a proactive assessment tool to identify and predict potential impacts, mitigate the negative impacts on heritage values, and sustain the attributes conveying OUVs in WH assets. The growing demand for urban development and its potential impacts on cultural heritage properties underscores the necessity for the development of a targeted Heritage Impact Assessment methodology for urban development threats. To adequately address multiple impacts, this paper proposes a triangulation of a qualitative matrix for impact identification and a semi-quantitative indicator-based index for impact analysis and evaluation. The methodology is applied to the World Heritage property of Masjed-e Jame of Isfahan in Iran. In drawing upon this example, a systematic and integrated impact assessment procedure is developed to capture a broad category of potential impacts and their significance that is crucial for determining site-specific mitigation strategies and informed decision-making within the context of heritage management and sustainable urban development. Full article

Existing research has primarily focused on investigating barriers in developed countries, emphasising economic, technical, and governmental factors which impede the diffusion of green building practices. However, developing regions, including the Middle East, often must be represented in green building research. Understanding these region-specific barriers is important for developing tailored solutions. In addition, existing identified green building barriers have primarily been obtained from the industry sector, while perspectives from other stakeholders, such as academia, have less attention. Hence, this study compares the perspectives of academic and industry professionals regarding the possible barriers which may impede the adoption of green buildings, with a particular focus on cultural, educational, and social factors. A mixed-method approach was employed, including a large-scale survey (n = 1112) with 54% of the participants being from the industrial sector and 46% being from the academic sector, as well as 17 semi-structured interviews to triangulate the data obtained from the survey. The study was conducted in Saudi Arabia as a representative case of the Middle East. Participants reported 23 barriers, which were themed into six groups: economic, technical, governmental, market demand, educational, and cultural barriers. Notably, seven of these barriers were reported for the first time in this study, including a lack of integrating green building concepts into university curricula, cultural preferences for traditional construction practices, resistance to change, prioritisation of economic factors over environmental and social considerations, a limited number of completed green building projects, delays in the permit and approval processes, and a lack of leadership and coordination. The statistical analysis revealed significant differences between the industry and academic perspectives (p < 0.05, d = 0.61) regarding the barriers to adopting green buildings, with academics over-reporting the educational, cultural, and technical barriers compared with the industry sector. Based on the identified barriers, five strategies were suggested which could help promote the widespread adoption and long-term sustainability of green buildings in the Middle East. Full article

The main shaft of a wind turbine is a critical component that ensures the normal operation of the turbine, and its axial displacement directly impacts its efficiency and safety. The inaccurate measurement of axial displacement may lead to severe issues such as shaft fractures, causing turbine shutdowns. Correcting measurement errors related to axial displacement is essential to prevent potential accidents. This study proposes an improved error correction method for measuring the axial displacement of wind turbine main shafts. Using a position-sensitive detector (PSD) and laser triangulation, the axial and radial displacements of the main shaft are measured to address environmental interference and cost constraints. Additionally, a Sparrow Search Algorithm- Backpropagation (SSA-BP) model is constructed based on operational data from the wind turbine’s main shaft to correct the system’s nonlinear errors. The Sparrow Search Algorithm (SSA) is employed to optimize the weights and thresholds of the Backpropagation (BP) neural network, enhancing prediction accuracy and model stability. Initially, a main shaft displacement measurement system based on a precision displacement stage was developed, and system stability tests and displacement measurement experiments were conducted. The experimental results demonstrate that the system stability error is ±0.025 mm, which is lower than the typical error of 0.05 mm in contact measurement. After model correction, the maximum nonlinear errors of the axial and radial displacement measurements are 0.83% and 1.29%, respectively, both of which are lower than the typical measurement error of 2% in contact measurements. This indicates that the proposed model can reliably and effectively correct the measurement errors. However, further research is still necessary to address potential limitations, such as its applicability in extreme environments and the complexity of implementation. Full article

This case study analyzes how Qatar rapidly achieved dairy self-sufficiency through public–private partnerships following the 2017–2021 blockade. Specifically, it examines the role of Baladna, Qatar’s leading dairy company, in scaling up its domestic production through alignment with government policies. A mixed-methods approach was employed, combining semi-structured interviews with key stakeholders from the Qatari government and Baladna and a review of Baladna’s internal documents and reports. Thematic content analysis was used to identify key themes, and data from Baladna’s reports were triangulated to validate the findings. Collaboration between Qatar’s government and Baladna ensured the self-sufficiency of domestic dairy demand, expanding operations with new products and exports, and strengthening supply chains. However, reliance on government support raises sustainability concerns, highlighting the need for efficiency and diversification. This partnership aligns with national policies, such as the Qatar National Food Security Strategy 2018–2023, and offers insights into how public–private collaborations can promote growth and supply security while balancing state support with market dynamics. This case study highlights how the blockade crisis catalyzed effective public–private collaboration, driving rapid growth in Qatar’s dairy sector to meet domestic demand. The lessons from Qatar’s developmental approach can provide insights for resource-rich countries struggling with food insecurity. Full article

The precise localization of epileptic foci with the help of EEG or iEEG signals is still a clinical challenge with current methodology, especially if the foci are not close to individual electrodes. On the research side, dipole reconstruction for focus localization is a topic of recent and current developments. Relatively low numbers of recording electrodes cause ill-posed and ill-conditioned problems in the inversion of lead-field matrices to calculate the focus location. Estimations instead of tissue conductivity measurements further deteriorate the precision of location tasks. In addition, time-resolved phase shifts are used to describe connectivity. We hypothesize that correlations over runtime approaches might be feasible to predict seizure foci with adequate precision. In a case study on EEG correlation in a healthy subject, we found repetitive periods of alternating high correlation in the short (20 ms) and long (300 ms) range. During these periods, a numerical determination of proportions of predominant latency and, newly established here, directionality is possible, which supports the identification of loops that, according to current opinion, manifest themselves in epileptic seizures. In the future, this latency and directionality analysis could support focus localization via dipole reconstruction using new triangulation calculations. Full article

This paper presents an overview of research results on the physical and technological features of crystal formation with an ordered distribution of vacancies. It is noted that the composition and properties of complex chalcogenide phases are not always described by the traditional concepts behind Kroeger’s theory. Model concepts are considered in which the carriers of properties in the crystalline state are not molecules, but an elementary crystalline element with a given arrangement of nodes with atoms and vacancies. It is established that the introduction of the term “quasi-element atom” of the zero group for a vacancy allows us to predict a number of compounds with an ordered distribution of vacancies. Examples of the analysis of peritectic multicomponent compounds and solid solutions based on them are given. Quasi-crystalline concepts are applicable to perovskite materials used in solar cells. It is shown that the photoluminescence of perovskite lead-cesium halides is determined by crystalline structural subunits i.e., the anionic octets. This is the reason for the improvement in the luminescent properties of colloidal quantum CsPbBr₃ dots under radiation exposure conditions. Full article

Case study to investigate whether creative writing through story-based learning in public and private secondary schools can account for performance in readability, purpose, word/sentence relationships, vocabulary diversity, correct use of punctuation marks and proper use of spelling rules. The exclusion criteria, applied only to public and private secondary school students, first, second and third periods. The sampling is convenient as the participants were selected from accessible educational institutions. This is a cross-sectional study of descriptive qualitative cut in which the coding of linguistic patterns and dominant themes is used. When triangulated with statistical results it was found that despite the variability in the results there was a production of original narratives, which corroborates the theories about the relationship between creativity and divergent thinking. It is confirmed that ABH is an active methodology based on the emotional link with creative writing from which components of the structure and creation of the narrative are derived, and it was found that most of the students are in a zone of proximal development, i.e., they are ready to learn with the help of a tutor or more advanced partner. Full article

Assessing the completeness of an underwater 3D reconstruction on-site is crucial as it allows for rescheduling acquisitions, which capture missing data during a mission, avoiding additional costs of a subsequent mission. This assessment needs to rely on a dense point cloud since a sparse cloud lacks detail and a triangulated model can hide gaps. The challenge is to generate a dense cloud with field-deployable tools. Traditional dense reconstruction methods can take several dozen hours on low-capacity systems like laptops or embedded units. To speed up this process, we propose building the dense cloud incrementally within an SfM framework while incorporating data redundancy management to eliminate recalculations and filtering already-processed data. The method evaluates overlap area limits and computes depths by propagating the matching around SeaPoints—the keypoints we design for identifying reliable areas regardless of the quality of the processed underwater images. This produces local partial dense clouds, which are aggregated into a common frame via the SfM pipeline to produce the global dense cloud. Compared to the production of complete dense local clouds, this approach reduces the computation time by about 70% while maintaining a comparable final density. The underlying prospect of this work is to enable real-time completeness estimation directly on board, allowing for the dynamic re-planning of the acquisition trajectory. Full article