Search Results (1,791)

This paper addresses the challenges of improving last-mile logistics delivery satisfaction in urban areas by studying a multi-trip vehicle routing problem with multiple delivery locations (MTVRPMDL). The MTVRPMDL simultaneously decides the visiting order of customers for each vehicle and selects an appropriate delivery location for every customer. The problem exhibits intrinsic spatial and decision symmetries, arising from interchangeable vehicle trips, alternative delivery locations for each customer, and symmetric route permutations that lead to equivalent operational outcomes. A mixed-integer programming model is proposed, aiming to minimize the total vehicle travel time. Within an iterated local search framework, a modified Solomon greedy insertion heuristic suitable for multi-delivery address and multi-trip settings is developed to generate initial solutions. During the iterative search phase, Or-opt and Relocate local search operators are employed, together with random swap perturbations, to enhance solution exploration. Computational experiments confirm the efficiency of the proposed model and algorithm, showing that allowing customers to have multiple delivery locations can significantly reduce overall travel time and improve the flexibility of vehicle routing decisions. Full article

The efficient and timely management of human evacuation during emergency events is an important area of research where the Internet of Things (IoT) can be of great value. Significant areas of application for optimum evacuation strategies include buildings, sports arenas, cultural venues, such as museums and concert halls, and ships that carry passengers, such as cruise ships. In many cases, the evacuation process is complicated by constraints on space and movement, such as corridors, staircases, and passageways, that can cause congestion and slow the evacuation process. In such circumstances, the Internet of Things (IoT) can be used to sense the presence of evacuees in different locations, to sense hazards and congestion, to assist in making decisions based on sensing to guide the evacuees dynamically in the most effective direction to limit or eliminate congestion and maximize safety, and notify to the passengers the directions they should take or whether they should stop and wait, through signaling with active IoT devices that can include voice and visual indications and signposts. This paper uses an analytical queueing network approach to analyze an emergency evacuation system, and suggests the use of the Pull Policy, which employs the IoT to direct evacuees in a manner that reduces downstream congestion by signalling them to move forward when the preceding evacuees exit the system. The IoT-based Pull Policy is analyzed using a realistic representation of evacuation from an existing commercial cruise ship, with a queueing network model that also allows for a computationally very efficient comparison of different routing rules with wide-ranging variations in speed parameters of each of the individual evacuees.Numerical examples are used to demonstrate its value for the timely evacuation of passengers within the confined space of a cruise ship. Full article

The ancient city of Gela (built in the 7th century BCE) is located in the southern sector of the Sicily Island (Southern Italy) on a Pleistocene marine terrace near the mouth of the Gela River. Gela was one of the most important Greek colonies in the Mediterranean Sea, strategically positioned at the crossroads of the major maritime trade routes and with a rich production of cereals thanks to the fertile Gela River alluvial plain. To reconstruct the coastal and environmental configuration during the Greek period and to improve the understanding of the location of the harbour basin, a multidisciplinary approach was applied to a sector of the Gela River alluvial–coastal plain. This area, located very close to the ancient city, is known as Conca (Italian for “Basin”) and was identified through the analysis of historical and modern maps as well as aerial photographs. The multidisciplinary approach includes geomorphology (derived from maps and aerial photos), stratigraphy (boreholes and archeological trench), paleoecology (ostracoda, foraminifera and fossil contents of selected layers), geochronology (¹⁴C dating of selected organic materials) and archeology (historical sources and maps, pottery fragments extracted from boreholes and trench layers). The main results show that this area was occupied by lower shoreface environments in the time intervals between 4.4 and 2.8 ka, which progressively transitioned to upper shoreface environments until the Greek age. During the Roman period, these environments were significantly reduced due to repeated alluvial sedimentation of the Gela River transforming the area into fluvial–marshy environments. A time interval of aeolian sand deposition was recorded in the upper part of the coastal stratigraphical succession, which can be related to climatic conditions with high aridity. Available data show that marine environments persisted in the Conca sector during the Greek age, allowing hypothesizing the presence of an ancient harbour in this area. The depth of the Greek age marine environments is estimated to be between 4.5 and 7 m below the current ground level. Further investigation, mainly based on geophysical and stratigraphical methods, will be planned aimed at identifying the presence of buried archeological targets. Full article

Background/Objectives: Craniopharyngiomas (CPs) are rare, generally benign tumors predominantly located in the sellar and suprasellar regions, associated with significant morbidity and complex surgical management. Despite high overall survival rates, patients frequently experience complications including visual impairment, pituitary dysfunction, diabetes insipidus (DI), and hypothalamic syndrome. Among these, hypothalamic obesity (HO) represents one of the most clinically challenging sequelae, often occurring early, lacking standardized medical treatment, and leading to substantial comorbidity and reduced quality of life. This study reports a single-center experience focusing on the relationship between skull base anatomy, surgical approach selection, and endocrinological outcomes. Methods: A retrospective analysis was conducted on patients diagnosed with CPs who underwent surgery by a dedicated team at our Department from January 2014 to January 2024. The approaches used were endoscopic (ER) and transcranial (TR). Preoperative imaging (volumetric MRI and CT scans) was analyzed using 3DSlicer (open-source software) for anatomical modeling of the tumor and skull base. Clinical outcomes were evaluated through follow-up assessments by a team of neuroendocrinologists. Data on BMI changes, DI onset, and hypopituitarism were collected. Statistical analyses consisted of descriptive comparisons and exploratory regression models. Results: Of 18 patients reviewed, 14 met the inclusion criteria. Larger sphenoid sinus volumes were associated with selection of an endoscopic endonasal approach (p = 0.0351; AUC = 0.875). In ER cases, the osteotomy area was directly related to tumor volume, independent of other anatomical parameters. Postoperatively, a significant increase in BMI (22.39 vs. 26.65 kg/m²; p = 0.0049) and in the incidence of DI (three vs. nine cases; p-value 0.0272) was observed. No clear differential association between surgical approach and endocrinological outcomes emerged in this cohort. Conclusions: Quantitative assessment of skull base anatomy using 3D modeling may support surgical approach selection in patients with craniopharyngiomas, particularly in identifying anatomical settings favorable to endoscopic endonasal surgery. Endocrinological outcomes appeared more closely related to tumor characteristics and hypothalamic involvement than to the surgical route itself. These findings support the role of individualized, anatomy-informed surgical planning within a multidisciplinary framework. Full article

This paper proposes a large-scale, self-healing multipoint fiber Bragg grating (FBG) sensor network that employs reinforcement learning (RL) techniques to enhance the resilience and efficiency of optical wireless communication networks. The system features a mesh-structured, self-healing ring-mesh architecture employing 2 × 2 optical switches, enabling robust multipoint sensing and fault tolerance in the event of one or more link failures. To further extend network coverage and support distributed deployment scenarios, free-space optical (FSO) links are integrated as wireless optical backhaul between central offices and remote monitoring sites, including structural health, renewable energy, and transportation systems. These FSO links offer high-speed, line-of-sight connections that complement physical fiber infrastructure, particularly in locations where cable deployment is impractical. Additionally, RL-based artificial intelligence (AI) techniques are employed to enable intelligent path selection, optimize routing, and enhance network reliability. Experimental results confirm that the RL-based approach effectively identifies optimal sensing paths among multiple routing options, both wired and wireless, resulting in reduced energy consumption, extended sensor network lifespan, and improved transmission delay. The proposed hybrid FSO–fiber self-healing sensor system demonstrates high survivability, scalability, and low routing path loss, making it a strong candidate for future services and mission-critical applications. Full article

Anime pilgrimage refers to the act of fans visiting real-world locations featured in anime works, offering visual familiarity alongside cultural depth. However, existing studies on anime tourism provide limited computational support for selecting pilgrimage sites based on contextual and experiential factors. This study proposes an intelligent recommendation framework based on multi-source data fusion that integrates three key elements: transportation accessibility, seasonal alignment between the current environment and the anime’s depicted scene, and a Cross-Platform Popularity Index (CPPI) derived from major global platforms. We evaluate each pilgrimage location using route-based accessibility analysis, season-scene discrepancy scoring, and robustly normalized popularity metrics. These factors are combined into a weighted Multi-Criteria Decision Making (MCDM) model to generate context-aware recommendations. To rigorously validate the proposed approach, a user study was conducted using a ranking task involving popular destinations in Tokyo. Participants were presented with travel conditions, spatial relationships, and popularity scores and then asked to rank their preferences. We used standard ranking-based metrics to compare system-generated rankings with participant choices. Furthermore, we conducted an ablation study to quantify the individual contribution of accessibility, seasonality, and popularity. The results demonstrate strong alignment between the model and user preferences, confirming that incorporating these three dimensions significantly enhances the reliability and satisfaction of real-world anime pilgrimage planning. Full article

This study investigates flooding and erosion impacts and human responses in Aoraki Mount Cook and Westland Tai Poutini national parks in Aotearoa New Zealand. These fast-eroding landscapes provide important test cases and insights for considering the public access dimensions of climate change. Our objectives were to explore and characterise the often-overlooked role of public access as a ubiquitous concern for protected areas and other area-based conservation approaches that facilitate connections between people and nature alongside their protective functions. We employed a mixed-methods approach including volunteered geographic information (VGI) from a park user survey (n = 273) and detailed case studies of change on two iconic mountaineering routes based on geospatial analyses of digital elevation models spanning 1986–2022. VGI data identified 36 adversely affected locations while 21% of respondents also identified beneficial aspects of recent landscape changes. Geophysical changes could be perceived differently by different stakeholders, illustrating the potential for competing demands on management responses. Impacts of rainfall-triggered erosion events were explored in case studies of damaged access infrastructure (e.g., roads, tracks, bridges). Adaptive responses resulted from formal or informal (park user-led) actions including re-routing, rebuilding, or abandonment of pre-existing infrastructure. Three widely transferable dimensions of public access management are identified: providing access that supports the core functions of protected areas; evaluating the impacts of both physical changes and human responses to them; and managing tensions between stakeholder preferences. Improved attention to the role of access is essential for effective climate change adaptation in parks and reserves. Full article

The Wua-Lai silvercraft community in Chiang Mai is experiencing a widening disconnect with younger visitors, raising concerns about the erosion of intangible cultural heritage. This study evaluates “Silver Craft Journey,” a location-based augmented reality (LBAR) system designed to revitalize cultural engagement and enhance cultural-heritage experience through context-aware, gamified exploration. A quasi-experimental field study with 254 participants across three age groups examined the system’s impact on cultural-heritage experience, knowledge acquisition, and real-world engagement. Results demonstrate substantial knowledge gains, with a mean increase of 7.74 points (SD = 4.37) and a large effect size (Cohen’s d = 1.77), supporting the effectiveness of LBAR in supporting tangible and intangible heritage understanding. Behavioral log data reveal clear age-related engagement patterns: older participants (41–51) showed declining mission completion rates and reduced interaction times at later points of interest, which may reflect increased cognitive and physical demands during extended AR navigation under real-world conditions. These findings underscore the potential of location-based AR to enhance cultural-heritage experience in real-world settings while highlighting the importance of age-adaptive interaction and route-design strategies. The study contributes a replicable model for integrating digital tourism, embodied AR experience, and community-based heritage preservation. Full article

Traditional routing algorithms optimizing for distance or travel time are inadequate for electric vehicles (EVs), which require energy-aware planning considering battery constraints and charging infrastructure. This work presents an energy-optimal routing system for EVs that integrates personalized consumption modeling with real-time environmental data. The system employs a Long Short-Term Memory (LSTM) neural network to predict State-of-Charge (SoC) consumption from real-world driving data, learning directly from spatiotemporal features including velocity, temperature, road inclination, and traveled distance. Unlike physics-based models requiring difficult-to-obtain parameters, this approach captures nonlinear dependencies and temporal patterns in energy consumption. The routing framework integrates static map data, dynamic traffic conditions, weather information, and charging station locations into a weighted graph representation. Edge costs reflect predicted SoC drops, while node penalties account for traffic congestion and charging opportunities. An enhanced A* algorithm finds optimal routes minimizing energy consumption. Experimental validation on a Nissan Leaf shows that the proposed end-to-end SoC estimator significantly outperforms traditional approaches. The model achieves an RMSE of 36.83 and an $R^2$ of 0.9374, corresponding to a 59.91% reduction in error compared to physics-based formulas. Real-world testing on various routes further confirms its accuracy, with a Mean Absolute Error in the total route SoC estimation of 2%, improving upon the 3.5% observed for commercial solutions. Full article

To address the current reliance on manual labor in traditional logistics sorting operations, which leads to low sorting efficiency and high operational costs, this study presents the design of an unmanned logistics vehicle based on the Robot Operating System (ROS). To overcome bounding-box loss issues commonly encountered by mainstream video-stream image segmentation algorithms under complex conditions, the novel SMITE video image segmentation algorithm is employed to accurately extract key regions of mail items while eliminating interference. Extracted logistics information is mapped to corresponding grid points within a map constructed using Simultaneous Localization and Mapping (SLAM). The system performs global path planning with the A* heuristic graph search algorithm to determine the optimal route, autonomously navigates to the target location, and completes the sorting task via a robotic arm, while local path planning is managed using the Dijkstra algorithm. Experimental results demonstrate that the SMITE video image segmentation algorithm maintains stable and accurate segmentation under complex conditions, including object appearance variations, illumination changes, and viewpoint shifts. The PaddleOCR text recognition algorithm achieves an average recognition accuracy exceeding 98.5%, significantly outperforming traditional methods. Through the analysis of existing technologies and the design of a novel parcel-grasping control system, the feasibility of the proposed system is validated in real-world environments. Full article

This study discusses the issue of designing reverse curves, i.e. a geometric system consisting of two circular arcs (usually with different radii), directed in opposite directions and directly connected to each other. The design is performed in an appropriate local Cartesian coordinate system. The origin of this system is located at the point of intersection of adjacent main directions of the route. Unlike other geometric situations, reverse curves have three main directions, which significantly complicate the design process. The initial values of the radii of the reverse arcs must correspond to the existing system of main directions. The introduction of transition curves causes these radii to decrease; their values are determined iteratively. A set of formulas for creating a geometric system of reverse curves is presented. These formulas were used in the calculation example. A graph of the horizontal curvature of the track axis and a method for determining the possible train speed, both without the use of cant on an arc and with the use of cant, are shown. The presented procedure is universal and can be applied to other geometric situations involving the design of reverse curves. It is also necessary to emphasize the practical usefulness of the discussed method not only in the design process, but also to pay attention to the cognitive value of the article. Full article

Wind and sand pose a significant threat to operational safety along the route of the Golmud-Korla Railway. To combat the adverse effects of these hazards, numerous sand retaining dikes and sand intercepting ditches have been constructed along the railway corridor. However, the deposition and erosion mechanisms of sand particles in close proximity to these structures have yet to be fully investigated. Therefore, it uses numerical simulations to study the structure of the wind-sand flow field around the sand retaining dike and the sand intercepting ditch, under varying spacing conditions, with an analysis of sand deposition and erosion laws. The results indicate that vortices form on the leeward side and within the sand intercepting ditch. Among these, the vortex flow occurring on the downstream side of the sand retaining dike exhibits a flow reattachment phenomenon at specific locations (i.e., attachment points). As the spacing increases, clockwise vortices Rd1 and Rd2, develop on the leeward side and inside the ditch, respectively. The leeward side of the spacing range of 0–8H is characterized by reverse erosion and deposition processes. When the spacing is 10–15H, a forward erosion zone emerges and expands progressively with the increase in spacing. When the spacing exceeds 10H, i.e., as the sand intercepting ditch is positioned downstream of the vortex reattachment point of the sand retaining dike, its sand interception efficiency is markedly enhanced. It not only elucidates the wind-sand flow and deposition patterns surrounding sand retaining dike and sand intercepting ditch under various spacing configurations but also offers valuable insights for the future design and implementation of protective structures for railways in wind-sand affected regions. Full article

This study developed a fire evacuation simulation model for a six-level underground station to evaluate evacuation efficiency under both dynamic and static conditions, including structural damage, smoke propagation, and real-time crowd congestion. Two representative pathfinding algorithms, Dijkstra’s and A*, were applied to analyze evacuation performance across eight fire scenarios occurring at different locations within the station. When only static factors were considered, both algorithms yielded identical maximum evacuation times, indicating comparable performance. However, the A* algorithm exhibited a significantly shorter computation time than Dijkstra’s, demonstrating higher operational efficiency. When dynamic variables such as real-time congestion and smoke-induced visibility reduction were introduced, the maximum evacuation times varied irregularly between the two algorithms. This outcome suggests that, under dynamic fire conditions, route guidance based solely on current information rather than predictive modeling may lead to suboptimal evacuation outcomes. Therefore, this study emphasizes the importance of establishing a predictive disaster management system capable of forecasting fire and smoke propagation, as well as a centralized control system that can dynamically distribute evacuees to enhance evacuation efficiency in deep underground stations. Full article

Out-of-hospital cardiac arrest (OHCA) is a major cause of death during mountain activities in the Alpine regions. Due to the time-critical nature of these emergencies and the logistical challenges of remote terrain, emergency medical services (EMS) are investigating the use of unmanned aerial vehicles (UAVs) to deliver automated external defibrillators (AEDs). This study presents a geospatial strategy for optimising AED delivery by UAVs in mountainous environments, using the Province of South Tyrol, Italy, as a model region. A Geographic Information System (GIS) framework was developed to identify suitable sites for vertical drone ports based on terrain, infrastructure, and regulatory constraints. A Low-Altitude-Flight Elevation Model (LAFEM) was implemented to generate obstacle-avoiding, regulation-compliant 3D flight paths using least-cost path analysis. The results identified 542 potential vertical-port locations, covering approximately 49% of South Tyrol within ten minutes of flight, and demonstrated significant time savings for AED delivery in field tests compared with manual and Euclidean routing. These findings show that integrating GIS-based vertical-port placement and terrain-adaptive UAV routing can substantially improve AED accessibility and response times in mountainous regions. The LAFEM model aligns with U-space airspace regulations and supports safe, automated AED deployment for improved outcomes in OHCA emergencies. Full article

The automation of logistics processes in companies is an essential part of the modernization and advancement of companies around the world. This article deals with the issue of deploying a selected type of automated guided vehicle (AGV) in very specific conditions. AGV is suitable for optimizing the circular supply chain in specific conditions of a manufacturing company. The deployment of AGVs is governed by the production needs of the section in question. The selection criterion was therefore the quantity of products that needed to be transported on the selected route. The article uses a new calculation of AGV requirements based on the saturation of individual components from the picking location to the assembly line. The ratio indicator was considered: driving time per shift, depending on the length of working time. Based on this calculation, the most effective option was applied from the individual solutions. Based on our calculation, we arrived at a requirement for three AGVs, plus a reserve, i.e., four. Our selected calculations were applied to the FRONT and TOP positions, where a decision was made between the option of using under-run AGVs or a truck. The decision was made based on the saturation level, and the result is described at the end of the discussion. The AGV is one of the tools for sustainable supply chain management in a company. However, it is important to evaluate the total cost of ownership, including lower labour costs, less risk of damage to goods, higher productivity, and long service life of the trucks. Thanks to these factors, AGVs often prove to be economically advantageous. Full article