Fast Route Research Articles

Analisis Area Jangkauan dan Rute Tercepat Menuju Pusat Fasilitas Kesehatan di Kota Denpasar

Fast and accurate healthcare services, particularly in emergency situations, are highly influenced by the effectiveness of access to health facilities. Therefore, geographic accessibility becomes a key factor in improving both the accessibility and quality of services for the community. This study aims to map service coverage areas and determine the fastest routes to healthcare facilities in Denpasar City. The method employed is Network Analysis based on Geographic Information Systems (GIS), using QGIS 3.6 software. The analysis results indicate that there are 23 healthcare facilities evenly distributed across all subdistricts, all located within a 5 km radius of Sanglah Hospital. Distances to Sanglah Hospital range from 0.4 to 5 km, with estimated travel times between 0.48 and 6 minutes. The nearest facilities are RS Medika Prima II and RS Surya Husadha, located 0.4 km away with an estimated travel time of approximately 0.48 minutes, while RS Bhakti Rahayu is the farthest, at a distance of 5 km and a travel time of approximately 6 minutes. These findings provide important implications for evacuation route planning and the enhancement of spatially based emergency healthcare systems.

Nanoporous Copper Films via Dynamic Hydrogen Bubbling: A Promising SERS Substrate for Sensitive Detection of Methylene Blue

Cu-based nanomaterials have received considerable attention as promising and cost-effective substrates for surface-enhanced Raman spectroscopy (SERS) applications despite their relatively low enhancement factor (EF) compared to noble metals like gold and silver. In this study, a fast and affordable synthesis route is proposed to obtain a three-dimensional porous copper film (NPC) via an electrodeposition technique based on the dynamic hydrogen bubbling template (DHBT). Two sets of NPC film were synthesized, one without additives and the other with cetyltrimethylammonium bromide (CTAB). The impacts of deposition time on the NPCs’ porous morphology, thickness, and SERS performance were systematically investigated. With the optimal deposition time, the nanopore sizes could be tailored from 26.8 to 73 μm without additives and from 12.8 to 24 µm in the presence of CTAB. The optimal additive-free NPC film demonstrated excellent SERS performance at 180 s of deposition, while the CTAB-modified film showed strong enhancement at 120 s towards methylene blue (MB), a highly toxic dye, achieving a detection limit of 10−6 M. Additionally, the samples with CTAB showed better efficiency than those without CTAB. The calculated EF of NPC was found to be 5.9 × 103 without CTAB and 2.5 × 103 with the CTAB, indicating the potential of NPC as a cost-effective candidate for high-performance SERS substrates. This comprehensive study provides insights into optimizing the structural morphology of the NPCs to maximize their SERS enhancement factor and improve their detection sensitivity toward MB, thus overcoming the limitations associated with conventional copper-based SERS substrates.

Next-Gen Travel Safety for Women: Integrating Advanced Technologies for Enhanced Security

Abstract- Next-Gen Travel Safety for Women: Integrating Advanced Technologies for Enhanced Security Abstract Ensuring safe travel on roads with automobiles or cabs is crucial for creating secure urban environments. Women traveling face significant risks, including harassment, unwanted physical touch, kidnapping, and assault. Often, the shortest or fastest route is not necessarily the safest. Users may prefer a slightly longer route if it means avoiding these dangers. Current navigation systems like Google Maps, Apple Maps, and Bing Maps fall short in addressing safety concerns such as theft, eve-teasing, snatching, hijacking, robbery, and more. These systems typically overlook safety factors in route planning. With rising urban crime rates, addressing safety and security for women has become a pressing concern. To tackle this challenge, this project introduces an innovative Travelers Safety Solution, utilizing advanced technologies to enhance the safety and experience of women commuters. By integrating Google Maps API, YOLOv8 for object detection, Tesseract OCR for text recognition, and connectivity with RTO servers, the system offers a comprehensive safety framework. Key features include route planning based on real-time traffic data, driver communication, SMS notifications with critical journey details, and real-time location tracking. The system actively monitors route deviations using map-matching algorithms, triggering immediate emergency alerts if deviations occur, notifying both the user and their emergency contacts. Additionally, users can review and provide feedback on driver performance post-journey. This solution not only addresses the safety concerns of women travelers but also empowers them with real-time information and communication, fostering a safer and more secure commuting experience.

Trust Violations Due To Error or Choice: The Differential Effects on Trust Repair in Human-Human and Human-Robot Interaction

Many decisions in life involve tradeoffs: to gain something, one often has to lose something in return. As robots become more autonomous, their decisions will extend beyond mere assessments (e.g., detecting a threat) to making choices (e.g., taking the faster or the safer route). The aim of the current research was to study perceived trustworthiness in scenarios involving adverse consequences due to 1) an assessment error, versus 2) a choice. Perceived trustworthiness (ability, benevolence, integrity) was measured repeatedly during a computer task simulating a military mission. Participants teamed with either a virtual human or a robotic partner who led the way and warned for potential danger. After encountering a hazard, the partner explained that it 1) failed to detect the threat (error) or 2) prioritized the mission and chose the fastest route despite the risk (choice). Results showed that: a) the error-explanation repaired all trustworthiness dimensions, b) the choice-explanation only repaired perceptions of ability, not benevolence or integrity, c) no differences were found between human and robotic partners. Our findings suggest that trust violations due to choices are harder to repair than those due to errors. Implications and future research directions are discussed.

QGIS Simulation Using Openstreetmap Data on Pedestrian Routes from Schools to Green Open Spaces

Green open spaces play an important role in modern urban development, benefiting both the ecology and the quality of life of city dwellers. Functional pedestrian path is an important element to support the accessibility of green open spaces. Commonly in Indonesia, green open spaces are isolated and disconnected from pedestrian path network. This research used spatial analysis combined with descriptive method to elaborate systematically and factually, regarding the accessibility of the fastest and shortest routes of pedestrian paths from selected schools to Lampung Elephant Park in Bandar Lampung, as the observed green open spaces. Authors suggested that the connection between schools and green open spaces is important in relation to facilitated environmental and physical education. Field observations and software simulation using QGIS based on OpenStreetMap were utilized to analyse the existing pedestrian path and to indicate the shortest routes. The simulation could suggest routes that accommodate comfortable walking times. The findings from this research can serve as valuable recommendations for urban planning, specifically aimed at enhancing pedestrian accessibility to green open spaces. Priority could be given to improving walking infrastructure along the proposed pedestrian pathways by closely addressing any unmet requirements. Future studies will explore advanced simulation techniques to further refine and optimize these recommendations.

In Situ Observation of Sustainable Hematite–Magnetite–Wüstite–Iron Hydrogen Plasma Reduction

Hydrogen plasma smelting reduction (HPSR) is an energy efficient, electrified, and fast process route to reduce not only iron ores but also thermally stable oxide materials, such as steelmaking sidestreams, waste, lean metallic ores, and metals with strong oxygen bonds. Both basic research of the underlying redox reaction mechanisms and upscaling and piloting of HPSR has gained significant momentum during the past decade, shedding light on reaction kinetics, hydrogen utilization, and process optimization. Yet, many questions still remain unanswered, the most important of which are how the reduction actually works at the interface between the hydrogen plasma and the oxidic and metal melts and what the actual radical species distribution is at the interface. Here, we present for the first time an in situ observation series of hematite reduction to metallic iron with filtered plasma imaging and optical emission spectroscopy. With the aid of plasma imaging and the optical spectra, the hematite, magnetite, wüstite, and both near-complete and complete metallization phases could be identified. The atomic hydrogen, iron, and aluminum species together with molecular optical emissions of FeO molecules were used to further analyze the process. Here, we study specifically hematite reduction to metallic iron at 10 pct H2/90 pct Ar in 450 and 900 mbar, and at 20 pct H2/80 pct Ar in 450 mbar as a model system.

Quantum Random Access Memory with Transmon-Controlled Phonon Routing.

Quantum random access memory (QRAM) promises simultaneous data queries at multiple memory locations, with data retrieved in coherent superpositions, essential for achieving quantum speedup in many quantum algorithms. We introduce a transmon-controlled phonon router and propose a QRAM implementation by connecting these routers in a treelike architecture. The router controls the motion of itinerant surface acoustic wave phonons based on the state of the control transmon, implementing the core functionality of conditional routing for QRAM. Our QRAM design is compact, supports fast routing operations, and avoids frequency crowding. Additionally, we propose a hybrid dual-rail encoding method to detect dominant loss errors without additional hardware, a versatile approach applicable to other QRAM platforms. Our estimates indicate that the proposed QRAM platform can achieve high heralding rates using current device parameters, with heralding fidelity primarily limited by transmon dephasing.

Rainfall–runoff modelling in a tropical climate (Citarum basin, West Java, Indonesia): Model and climate data intercomparison

ABSTRACT Hydrological research in tropical regions has been limited by a lack of high-quality precipitation and evapotranspiration input data, and high-quality observed runoff calibration data. Hence, most hydrological models have been developed for non-tropical regions and calibrated on non-tropical climatic data. To address these challenges, we assessed the performance of 24 rainfall–runoff models in combination with seven precipitation and three evapotranspiration datasets (504 combinations), in three catchments in the Citarum basin, Indonesia, to identify which models and input datasets were best suited to modelling daily mean flow in a volcanic region and tropical climate, and to assess the parameter sensitivity of the most suitable models. We found that model performance was most strongly affected by choice of input precipitation data and that the most suitable option was different for each of the three study catchments, varying over tens of kilometres. Hydrological model structure played a less significant role, and models developed explicitly for volcanic or tropical regions did not show a clear advantage over those designed for other regions or climates. However, models with two separate, parallel, fast and slow routing pathways had higher predictive skill than those with just one pathway in representing the year-round range of flow behaviours.

From Raw Data to 'Best' Travel Route Computation

This paper presents the processing of raw data for 'best' travel route computation and recommendation to consumers by a specially developed web application operating on top of the IoT platform EMULSION. Three different types of 'best' travel routes are computed for each journey requested by a consumer, namely the healthiest route, the fastest route, and the shortest route. The importance of the presented work lies within the practical applicability of the proposed method for processing raw data for just-on-time 'best' travel route computation and recommendation to consumers.

Dynamic Route Planning for Urban Green Mobility: Development of a Web Application Offering Sustainable Route Options to Commuters

Rising travel distances and worsening urban air quality underscore the need for improved route choices to reduce energy consumption and exposure. Whereas traditional route-planning systems focus mainly on distance and time, this study develops a methodology that provides users with wider choices in route selection. The paper presents a web-based tool designed to assist commuters in selecting eco-friendly routes. This tool combines a React.js frontend for intuitive user input with a Go back end that processes real-time data to rank and deliver route suggestions based on air pollution and energy consumption, in addition to distance and time. Real-time application programming interfaces from Mapbox are used for traffic conditions, and the World Air Quality Index is used for air-quality metrics, which are integrated into the GraphHopper multimodal routing engine. As a result, the tool offers five route choices: the shortest route, the fastest route, the route with the least exposure to air pollution (LEAP), the route with the least energy-consumption route (LECR), and a suggested route that considers all four parameters. Applied to Delhi, the tool demonstrates that the LEAP route can reduce exposure by up to 53%, although it may lead to a 42% increase in travel time in Central Delhi. This study is the first to showcase the LECR in India, demonstrating that selecting this route can save up to 28% of energy in South Delhi. Daily variability analysis conducted at different hours revealed that peak-hour times correlate with increased exposure and energy consumption. Although these results are initial and could be further enhanced with better data, the preliminary results are encouraging.

A GIS-based framework for routing decisions to reduce livestock disease exposure risk.

Safe and effective transportation of livestock during disease outbreaks is crucial for maintaining agricultural productivity and economic stability. This work offers a novel perspective on the transportation of hazardous biological materials within the veterinary field. In response to the complex challenges of managing livestock disease outbreaks, we evaluated different routing measures for safe land transport of diseased animals or infected materials. The potential disease exposure risk to susceptible livestock populations during hypothetical transportation scenarios of infected livestock and specimens was estimated. A GIS-based framework was developed to integrate and manage raster-based Gridded Livestock of the World (GLW) data and vector-based road network data, which was used to implement a time-based risk (TBR) measure to support routing decisions of diseased animals. This approach not only considers time as a traditional routing metric but also incorporates livestock population distribution as a crucial factor in the disease exposure risk assessment. Along with the TBR measure, the shortest, fastest, and least population exposure measures are also evaluated as routing solution benchmarks. Analysis results based on two origin-destination pairs within Oklahoma, USA demonstrate that the TBR measure yields routes with the least impact on animal populations as compared to the shortest, fastest, and least population route, especially over longer distances. Our results underscore the importance of incorporating dynamic exposure risks in routing decisions to effectively minimize potential disease spread to vulnerable populations distributed along the path of transportation. This study also highlights the potential of GIS in enhancing biosecurity and disease control measures by optimizing transportation routes that consider various risk factors.

Intelligent and automatic irrigation system based on internet of things using fuzzy control technology

Agriculture is a vital sector in the global economy but also a major contributor to water consumption and wastage due to inefficient irrigation techniques. To address this issue, smart irrigation systems using the Internet of Things (IoT) have emerged as a solution for optimizing water use. These systems utilize real-time sensor data to improve irrigation efficiency and agricultural productivity. This paper presents an automatic, low-cost intelligent irrigation system based on a fuzzy rule-based inference approach and an energy-aware routing algorithm. The proposed system determines the optimal irrigation method using sensor data and ensures efficient information transmission through a fast fuzzy-based routing mechanism. Additionally, it enables remote monitoring and control via mobile devices, enhancing user convenience. The system is designed to be intelligent, cost-effective, and portable, making it suitable for various agricultural applications such as greenhouses and farms. Simulation results demonstrate that the proposed method outperforms existing algorithms, including DLQR, SPIS, and FWIS, in terms of network lifetime and power consumption. By improving water efficiency and reducing resource wastage, this research contributes to sustainable agriculture. The proposed system provides a scalable and adaptable solution for modern farming, ensuring better irrigation management while conserving essential resources.

EV Charging Stations Management System using Al Chatbot

The rapid adoption of electric vehicles (EVs) has led to a growing demand for efficient EV charging station management around the world. Operated by Natural Language Processing (NLP) and Artificial Intelligence (AI), chatbots have been developed as valuable tools to improve the user experience and operational efficiency of EV charging stations. In this article, we examine existing research on chatbot integration in EV charging stations and explore the applications, benefits and challenges. Identify key areas of chatbot applications, including user support, operational monitoring, and secure payments, highlighting challenges such as integration complexity and concerns about data protection models. Future research instructions are discussed to improve these gaps and further improve EV station management. Along with the building of charging stations, automakers like as TATA have introduced new electric vehicles to the market. However, when the stations are fully utilized, delays may occur due to the current charging duration, which ranges from 15 to 30 minutes. To address these issues, our proposal calls for connecting all EV charging stations into a single network. Users can locate and select their preferred station with ease, which ultimately saves time and is particularly helpful when driving electric cars long distances. Users can reserve slots when they become available; if not, the system asks them to select a different time. A portion of the amount must be paid for the online booking confirmation. Additionally, our system provides charging stations with a management interface to govern reserved and open slots and displays the fastest route to the selected station. Our web-based application senses direction using the Google Maps API and time-slot allocation algorithms. An online payment gateway expedites transactions, and our chatbot technology allows voice commands to be utilized to control the program. Customers can save a great deal of time by using our technology to locate and reserve appropriate charging stations

Dependence of the magnetite (Fe<sub>3</sub>O<sub>4</sub>) and silica (SiO<sub>2</sub>) nanostructured heterojunction for the photodegradation of tartrazine yellow dye

This work investigated the photocatalytic properties of polymorphic nanostructures based on silica (SiO2) and magnetite (Fe3O4) for the photodegradation of tartrazine yellow dye. In this sense, a fast, easy, and cheap synthesis route was proposed that used sugarcane bagasse biomass as a precursor material for silica. The Fourier transform infrared (FTIR) spectroscopy results showed a decrease in organic content due to the chemical treatment with NaOH solution. This was confirmed through the changes promoted in the bonds of chromophores belonging to lignin, cellulose, and hemicellulose. This treated biomass was calcined at 800 ℃, and FTIR and X-ray diffraction (XRD) also confirmed the biomass ash profile. The FTIR spectrum showed the formation of silica through stretching of the chemical bonds of the silicate group (Si-O-Si), which was confirmed by DXR with the predominance of peaks associated with the quartz phase. Scanning electron microscopy (SEM) and energy dispersive X-ray spectroscopy (EDS) confirmed the morphological and chemical changes due to the chemical and thermal treatments applied to this biomass. Using the coprecipitation method, we synthesized Fe3O4 nanoparticles (Np) in the presence of SiO2, generating the material Fe3O4/SiO2-Np. The result was the formation of nanostructures with cubic, spherical, and octahedral geometries with a size of 200 nm. The SEM images showed that the few heterojunctions formed in the mixed material increased the photocatalytic efficiency of the photodegradation of tartrazine yellow dye by more than two times. The degradation percentage reached 45% in 120 min of reaction time. This mixed material can effectively decontaminate effluents composed of organic pollutants containing azo groups.

Development of Mobile GIS Based Digital Map Location Marking Application for Navigation Purposes

In today's digital era, map and navigation applications have become essential tools for users to find locations, obtain the fastest routes, and explore new places. Google Maps is one of the most popular and comprehensive mapping applications that offers various features, such as navigation. However, despite being highly beneficial, Google Maps has several limitations, particularly regarding map markers, personalized, creating individual routes, and offline map usage on navigation. To address these issues, this research develops an innovative application called StellarPath. StellarPath is a mobile-based digital map location marker application that adopts Location Based Service (LBS) methods for more effective navigation. This application focuses on offline usability as a digital map marker and includes features such as offline maps stored indefinitely, offline navigation, manual route creation, and higher personalization, allowing users to save and manage markers with additional information offline. Test results show a success rate of 92.5%, indicating the application's effectiveness. The conclusion drawn is that the application can download and store maps offline, although it has shortcomings in managing downloaded maps. The offline navigation feature allows users to draw, save, and manage manual routes on the map. Users can create and save location markers with additional information offline. Navigation is flexible, with the option to start navigation by tapping on the map and features that can be enabled or disabled. This research aims to provide a more flexible and personalized navigation solution compared to existing standard map and navigation applications, such as Google Maps.

Realizing a Robust High-Performance Ni-GDC Nanocomposite Anode for SOFCs by Self-Assembly of Reactive Cosputtered Nanolayers.

This study reports a fast and scalable route for fabricating efficient and durable SOFCs, leveraging nickel oxide-gadolinium-doped ceria (NiO-GDC) nanocomposites and thin-film electrolytes based on reactive sputtering. The Ni and GdCe targets are first cosputtered to form films with a stack-layered structure of metallic Ni and GDC, followed by sputtering YZr and GdCe targets alternatively to make multilayer electrolytes. By annealing the sputtered anode-electrolyte assembly with the La0.6Sr0.4Co0.2Fe0.8O3-δ cathode in a single step at 1000 °C, full cells feature heterostructure ceramic multilayers; NiO-GDC nanocomposites with heterointerfaces are in situ constructed, while the multilayer electrolytes are fully dense. The electrochemical performance is significantly enhanced by the insertion of the NiO-GDC nanocomposite anode and the optimization of the film configuration, achieving a peak power density of 2.72 W cm-2 at 800 °C. Furthermore, no degradation is observed during the stability test, and the fine porous nanostructure of the Ni-GDC anode is preserved.

A Fast Three-layer One-side Bottleneck Channel Routing with Layout Constraints using ILP

A Fast Three-layer One-side Bottleneck Channel Routing with Layout Constraints using ILP

Lean in logistics through autonomous last-mile delivery

Efficient last-mile delivery is essential in modern commerce, yet it poses challenges in timeliness, cost-effectiveness, and customer satisfaction. Between 41% and 53% of supply chain expenses, particularly in the United States, are attributed to this final leg. Autonomous technology, with its complex algorithms and driverless vehicles, is capable of revolutionizes last-mile delivery by optimizing routing and scheduling, reducing labor costs, and ensuring the fastest delivery routes. Real-time inventory management can further integrate lean principles into last-mile delivery, and therefore enhancing operational efficiency. This project explores the synergy between autonomous technology and lean concepts, aiming to eliminate non-value-added tasks, maximize resource utilization, and enhance overall efficiency, in terms of travel time reduction, with focuses specifically on develop countries with supporting technologies to support autonomous vehicles and robot technologies infrastructures in place. The research focused on leveraging available traffic data from autonomous technology can enable continuous improvement, enhancing productivity and customer satisfaction. Additionally, incorporating autonomous technology can enhance the reliability and safety of last-mile delivery operations through cost reduction, time reduction, and route flexibility. This research primarily examines the impact of traffic lights on traditional delivery vans, using New York City streets as a case study. A comprehensive model has been developed to quantify the cost implications of traffic light delays, providing a structured method to evaluate these inefficiencies. The model offers a practical approach that can be applied globally users simply need to input relevant parameters, and the system will compute the time, cost, and overall impact of such delays. Additionally, the study highlights the advantages of autonomous delivery systems, particularly drones, over conventional delivery methods. By utilizing this model, businesses and policymakers can make data-driven decisions to optimize last-mile logistics and enhance delivery efficiency. Recommendations include utilizing autonomous technology to meet environmental preservation requirements and offering eco-friendly delivery options. The convergence of lean principles and autonomous technologies offers transformative opportunities, enabling businesses to fulfill consumer demands, reduce costs, operate sustainably, and enhance efficiency.

Sistem Informasi Geografis Dengan Algoritma Dijkstra Untuk Menentukan Jarak Terdekat Pariwisata Di Kabupaten Pesawaran

Tourism plays an important role in the development of a region. Apart from introducing the area to a wider audience, tourism is also a major source of creating jobs and encouraging local economic growth. Pesawaran Regency, which was previously part of South Lampung Regency, is now a newly formed region. Its location close to Bandar Lampung City, the capital of Lampung Province, provides strategic value that can accelerate the development of the region. Distance problems and uncertainty in finding routes often become obstacles for many people when visiting various locations. Pesawaran Regency has a number of interesting tourist destinations, one of which is Pahawang Island, which is one of the leading tourist destinations. To make it easier for tourists, both local and international, the fastest route to these tourist destinations is needed. This research uses the Dijkstra algorithm to calculate the shortest distance from one point to the selected tourist destination in Pesawaran Regency. This article will review the application of the Dijkstra algorithm in finding the most efficient route for searching tourist locations in Pesawaran Regency. The research results show that this system can help tourists reach tourist locations more quickly.

Effect of Novel Fast Heating Processing Route on the Formation of Martensitic Microstructures and the Subsequent Impact on Mechanical Properties of 0.2–0.3%C Steels for Abrasion-Resistant Plates

Effect of Novel Fast Heating Processing Route on the Formation of Martensitic Microstructures and the Subsequent Impact on Mechanical Properties of 0.2–0.3%C Steels for Abrasion-Resistant Plates