Efficient Route Planning for Real-Time Demand-Responsive Transit

Demand Responsive Transit (DRT) responds to the dynamic users’ requests without any fixed routes and timetablesand determines the stop and the start according to the demands. This study explores the optimization of dynamicvehicle scheduling and real-time route planning in urban public transportation systems, with a focus on busservices. It addresses the limitations of current shared mobility routing algorithms, which are primarily designedfor simpler, single origin/destination scenarios, and do not meet the complex demands of bus transit systems. Theresearch introduces an route planning algorithm designed to dynamically accommodate passenger travel needsand enable real-time route modifications. Unlike traditional methods, this algorithm leverages a queue-based,multi-objective heuristic A∗ approach, offering a solution to the inflexibility and limited coverage of suburbanbus routes. Also, this study conducts a comparative analysis of the proposed algorithm with solutions based onGenetic Algorithm (GA) and Ant Colony Optimization Algorithm (ACO), focusing on calculation time, routelength, passenger waiting time, boarding time, and detour rate. The findings demonstrate that the proposedalgorithmsignificantly enhances route planning speed, achieving an 80–100-fold increase in efficiency over existingmodels, thereby supporting the real-time demands of Demand-Responsive Transportation (DRT) systems. Thestudy concludes that this algorithm not only optimizes route planning in bus transit but also presents a scalablesolution for improving urban mobility.

Stage at diagnosis of colorectal cancer through diagnostic route:Who should be screened?

BACKGROUND Colorectal cancer(CRC)is a global health concern,with advanced-stage diagnoses contributing to poor prognoses.The efficacy of CRC screening has been well-established;nevertheless,a significant proportion of patients remain unscreened,with>70%of cases diagnosed outside screening.Although identifying specific subgroups for whom CRC screening should be particularly recommended is crucial owing to limited resources,the association between the diagnostic routes and identification of these subgroups has been less appreciated.In the Japanese cancer registry,the diagnostic routes for groups discovered outside of screening are primarily categorized into those with comorbidities found during hospital visits and those with CRC-related symptoms.AIM To clarify the stage at CRC diagnosis based on diagnostic routes.METHODS We conducted a retrospective observational study using a cancer registry of patients with CRC between January 2016 and December 2019 at two hospitals.The diagnostic routes were primarily classified into three groups:Cancer screening,follow-up,and symptomatic.The early-stage was defined as Stages 0 or I.Multivariate and univariate logistic regressions were exploited to determine the odds of early-stage diagnosis in the symptomatic and cancer screening groups,referencing the follow-up group.The adjusted covariates were age,sex,and tumor location.RESULTS Of the 2083 patients,715(34.4%),1064(51.1%),and 304(14.6%)belonged to the follow-up,symptomatic,and cancer screening groups,respectively.Among the 2083 patients,CRCs diagnosed at an early stage were 57.3%(410 of 715),23.9%(254 of 1064),and 59.5%(181 of 304)in the follow-up,symptomatic,and cancer screening groups,respectively.The symptomatic group exhibited a lower likelihood of early-stage diagnosis than the follow-up group[P<0.001,adjusted odds ratio(aOR),0.23;95%confidence interval(95%CI):0.19-0.29].The likelihood of diagnosis at an early stage was similar between the follow-up and cancer screening groups(P=0.493,aOR for early-stage diagnosis in the cancer screening group vs follow-up group=1.11;95%CI=0.82-1.49).CONCLUSION CRCs detected during hospital visits for comorbidities were diagnosed earlier,similar to cancer screening.CRC screening should be recommended,particularly for patients without periodical hospital visits for comorbidities.

The Impact of Sea Level Rise on Roadway Design and Evacuation Routes in Delaware

As the global temperature continues to increase, the sea level continues to rise at a rapid rate that has never been seen before. This becomes an issue for many facets of life but one of the most impacted is the transportation infrastructure. Many people living in low elevation coastal areas can become trapped by flooding with no way in or out. With Delaware being a coastal state, this would affect a large portion of the population and will have detrimental effects over time if nothing is done to combat sea level rise. The issue with sea level rise in transportation is that once the roads become flooded, they become virtually unusable and detour routes would be needed. If all the roads in a coastal area were to be affected by sea level rise, the options for detours would become limited. This article looks at direct solutions to combat sea level rise and indirect solutions that would specifically help transportation infrastructure and evacuation routes in Delaware. There is not one solution that can fix every problem, so many solutions are laid out to see what is applicable to each affected area. Some solutions include defense structures that would be put close to the coast, raising the elevation of vulnerable roads throughout the state and including pumping stations to drain the water on the surface of the road. With an understanding of all these solutions around the world, the ultimate conclusion came in the form of a six-step plan that Delaware should take in order to best design against sea level rise in these coastal areas.

Track Bed Total Route Evaluation for Track Renewals&Asset Management“A Network Rail Perspective”

Over the last 10 years there have been significant developments and improvements in the understanding of railway track bed in the UK and its relationship and impact on track quality,ballast life and maintenance following track renewals.This paper aims to describe the process adopted by Network Rail for track bed investigation and design which offers Network Rail optimum design solutions and value for money from an investigation and construction perspective,balancing design with possession availability to maximise construction output.It also describes innovative investigation and construction techniques that have been developed over the last 5 years maximising the use of rail mounted asset condition data collection systems which run at line speed,allowing targeted investigations and in some case removing the requirements for physical site investigation.It also allows Network Rail to predict sections of track bed which may be affected by line speed increases which would cause the track bed to fail prematurely or,retain its ability to maintain good track geometry post line speed increase.These problems can manifest themselves as stiffness related problems such as critical velocity issues(surface wave velocity,Rayleigh Wave velocity)or,sub-grade erosion resulting in high rates of deterioration in the vertical track geometry.The paper also describes the development and installation process for Enhanced Axial Micropiles to address stiffness related track bed problems whilst leaving the track in-situ a technique which is new to the UK railways.

Manual Order Picking Route Optimization in Distribution Warehouse of Chain Furniture Retail Enterprise

Due to the effects of the COVID-19 pandemic and the rise of online shopping, the offline sales of IKEA Fuzhou have been declining since 2020. Because the cost of distribution warehouse is a major expense for offline chain furniture retailers, and the picking process is a key activity in distribution warehouse operations. To reduce the cost of distribution warehouse and alleviate the survival pressure of the offline chain furniture retailers, this paper focuses on optimizing the picking route of the IKEA Fuzhou distribution warehouse. It starts by creating a two-dimensional coordinate system for the storage location of the distribution warehouse using the traditional S-type picking strategy to calculate the distance and time of the sorting route. Then, the problem of optimizing the picking route is then transformed into the travelling salesman problem (TSP), and picking route optimization model is developed using a genetic algorithm to analyze the sorting efficiency and picking route optimization. Results show that the order-picking route using the genetic algorithm strategy is significantly better than the traditional S-type picking strategy, which can improve overall sorting efficiency and operations, reduce costs, and increase efficiency. Thus, this establishes an implementation process for the order-picking path based on genetic algorithm optimization to improve overall sorting efficiency and operations, reduce costs, increase efficiency, and alleviate the survival pressure of pandemic-affected enterprises.

CoopAI-Route: DRL Empowered Multi-Agent Cooperative System for Efficient QoS-Aware Routing for Network Slicing in Multi-Domain SDN

The emergence of beyond 5G networks has the potential for seamless and intelligent connectivity on a global scale.Network slicing is crucial in delivering services for different,demanding vertical applications in this context.Next-generation applications have time-sensitive requirements and depend on the most efficient routing path to ensure packets reach their intended destinations.However,the existing IP(Internet Protocol)over a multi-domain network faces challenges in enforcing network slicing due to minimal collaboration and information sharing among network operators.Conventional inter-domain routing methods,like Border Gateway Protocol(BGP),cannot make routing decisions based on performance,which frequently results in traffic flowing across congested paths that are never optimal.To address these issues,we propose CoopAI-Route,a multi-agent cooperative deep reinforcement learning(DRL)system utilizing hierarchical software-defined networks(SDN).This framework enforces network slicing in multi-domain networks and cooperative communication with various administrators to find performance-based routes in intra-and inter-domain.CoopAI-Route employs the Distributed Global Topology(DGT)algorithm to define inter-domain Quality of Service(QoS)paths.CoopAI-Route uses a DRL agent with a message-passing multi-agent Twin-Delayed Deep Deterministic Policy Gradient method to ensure optimal end-to-end routes adapted to the specific requirements of network slicing applications.Our evaluation demonstrates CoopAI-Route’s commendable performance in scalability,link failure handling,and adaptability to evolving topologies compared to state-of-the-art methods.

Frequency-tunable single-photon router based on a microresonator containing a driven three-level emitter

We propose a frequency-tunable router of single photons with high routing efficiency, which is constructed by two waveguides mediately linked by a single-mode whispering gallery resonator with a driven three-level emitter. Quantum routing probability in the output port is obtained via the real-space Hamiltonian. By adjusting the resonator–emitter coupling and the drive, the desired continuous central frequencies for the resonance peaks of routing photons can be manipulated nearly linearly, with the assistance of Rabi splitting effect and optical Stark shift. The proposed routing system may provide potential applications in designing other frequency-modulation quantum optical devices, such as multiplexers,filters, and so on.

The Influence of Price Discrimination from Airports on the Route Development Behavior of Airlines

Given the prominence and magnitude of airport incentive schemes,it is surprising that literature hitherto remains silent as to their effectiveness.In this paper,the relationship between airport incentive schemes and the route development behavior of airlines is analyzed.Because of rare and often controversial findings in the extant literature regarding relevant influencing variables for attracting airlines at an airport,expert interviews are used as a complement to formulate testable hypotheses in this regard.A fixed effects regression model is used to test the hypotheses with a dataset that covers all seat capacity offered at the 22 largest German commercial airports in the week 46 from 2004 to 2011.It is found that incentives from primary choice,as well as secondary choice airports,have a significant influence on Low Cost Carriers.Furthermore,Low Cost Carriers,in general,do not leave any of both types of airports when the incentives cease.In the case of Network Carriers,no case is found where one joins a primary choice airport and receives an incentive.Insufficient data between Network Carriers and secondary choice airports in the time when incentives have ceased means that no statement can be given.

Research on Optimizing the Construction of the Long March National Cultural Park from the Perspective of Cultural Route Heritage Protection

The idea of cultural route heritage protection expands the protection theory for world cultural heritage.The Long March route carries the prominent characteristic of cultural route heritage.By actively building the Long March National Cultural Park,China has strengthened the overall protection and integrated utilization of the Long March cultural heritage,upgraded the hardware facilities for exhibition,and investigated ways to protect cultural route heritage with Chinese characteristics.During the construction of the Park,it is necessary to draw on the concept and norms of the cultural route heritage protection,optimize the construction approach,and make the construction of the Park more in line with the linear cultural characteristics of Long March heritage.Specifically,it is proposed to improve the Long March cultural route heritage protection system oriented towards“authenticity”protection,to deeply tap and interpret the prominent universal worth of the Long March route,augmenting the international dissemination of the Long March culture in an innovative way,and realizing a more scientific and effective protection and utilization of Long March cultural resources.

Tourism Route Recommendation Based on A Multi-Objective Evolutionary Algorithm Using Two-Stage Decomposition and Pareto Layering

Tourism route planning is widely applied in the smart tourism field.The Pareto-optimal front obtained by the traditional multi-objective evolutionary algorithm exhibits long tails,sharp peaks and disconnected regions problems,which leads to uneven distribution and weak diversity of optimization solutions of tourism routes.Inspired by these limitations,we propose a multi-objective evolutionary algorithm for tourism route recommendation(MOTRR)with two-stage and Pareto layering based on decomposition.The method decomposes the multiobjective problem into several subproblems,and improves the distribution of solutions through a two-stage method.The crowding degree mechanism between extreme and intermediate populations is used in the two-stage method.The neighborhood is determined according to the weight of the subproblem for crossover mutation.Finally,Pareto layering is used to improve the updating efficiency and population diversity of the solution.The two-stage method is combined with the Pareto layering structure,which not only maintains the distribution and diversity of the algorithm,but also avoids the same solutions.Compared with several classical benchmark algorithms,the experimental results demonstrate competitive advantages on five test functions,hypervolume(HV)and inverted generational distance(IGD)metrics.Using the experimental results of real scenic spot datasets from two famous tourism social networking sites with vast amounts of users and large-scale online comments in Beijing,our proposed algorithm shows better distribution.It proves that the tourism routes recommended by our proposed algorithm have better distribution and diversity,so that the recommended routes can better meet the personalized needs of tourists.

Cooperative Channel and Optimized Route Selection in Adhoc Network

Over the last decade,mobile Adhoc networks have expanded dramati-cally in popularity,and their impact on the communication sector on a variety of levels is enormous.Its uses have expanded in lockstep with its growth.Due to its instability in usage and the fact that numerous nodes communicate data concur-rently,adequate channel and forwarder selection is essential.In this proposed design for a Cognitive Radio Cognitive Network(CRCN),we gain the confidence of each forwarding node by contacting one-hop and second level nodes,obtaining reports from them,and selecting the forwarder appropriately with the use of an optimization technique.At that point,we concentrate our efforts on their channel,selection,and lastly,the transmission of data packets via the designated forwarder.The simulation work is validated in this section using the MATLAB program.Additionally,steps show how the node acts as a confident forwarder and shares the channel in a compatible method to communicate,allowing for more packet bits to be transmitted by conveniently picking the channel between them.We cal-culate the confidence of the node at the start of the network by combining the reliability report for thefirst hop and the reliability report for the secondary hop.We then refer to the same node as the confident node in order to operate as a forwarder.As a result,we witness an increase in the leftover energy in the output.The percentage of data packets delivered has also increased.

Migration routes and differences in migration strategies of Whooper Swans between spring and autumn

Long-distance migratory birds travel more rapidly in spring than in autumn,as they face temporal breeding constraints.However,several species travel slower in spring owing to environmental influences,such as food availability and wind conditions.GPS trackers were attached to 17 Whooper Swans(Cygnus cygnus) inhabiting northeastern Mongolia,to determine their migration routes and stopover sites in spring and autumn.Differences between spring and autumn migrations,migration-influencing parameters,and the effect of spring stopover site temperatures were analyzed.Six swans completed perfect tours between their wintering and breeding sites,and these data were used for analysis.Spring migration lasted 57 days,with 49.2 days spent at 3.7 stopover sites.Autumn migration lasted 21.5 days,with 17.5 days spent at 1.0 stopover sites.Thus,the swans traveled more rapidly in autumn than in spring.Migration distance,number of stopovers,migration speed,and straightness were important migration determinants in both spring and autumn.Migration distance,stopover duration,number of stopovers,daily travel speed,travel duration,and migration speed differed significantly between spring and autumn.During spring migration,the temperature at the current stopover sites and that at the future stopover sites displayed significant variations(t=1585.8,df=631.6,p <0.001).These findings are critical for the conservation and management of Whooper Swans and their key habitats in East Asian regions,and the data are anticipated to make a particularly significant contribution toward developing detailed management plans for the conservation of their key habitats.

Regional variation in routes to diagnosis of cholangiocarcinoma in England from 2006 to 2017

BACKGROUND Incidence of cholangiocarcinoma(CCA)is rising,with overall prognosis remaining very poor.Reasons for the high mortality of CCA include its late presentation in most patients,when curative options are no longer feasible,and poor response to systemic therapies for advanced disease.Late presentation presents a large barrier to improving outcomes and is often associated with diagnosis via mergency presentation(EP).Earlier diagnoses may be made by Two Week Wait(TWW)referrals through General practitioner(GP).We hypothesise that TWW referrals and EP routes to diagnosis differ across regions in England.AIM To investigate routes to diagnosis of CCA over time,regional variation and influencing factors.METHODS We linked patient records from the National Cancer Registration Dataset to Hospital Episode Statistics,Cancer Waiting Times and Cancer Screening Programme datasets to define routes to diagnosis and certain patient characteristics for patients diagnosed 2006-2017 in England.We used linear probability models to investigate geographic variation by assessing the proportions of patients diagnosed via TWW referral or EP across Cancer Alliances in England,adjusting for potential confounders.Correlation between the proportion of people diagnosed by TWW referral and EP was investigated with Spearman’s correlation coefficient.RESULTS Of 23632 patients diagnosed between 2006-2017 in England,the most common route to diagnosis was EP(49.6%).Non-TWW GP referrals accounted for 20.5%of diagnosis routes,13.8%were diagnosed by TWW referral,and the remainder 16.2%were diagnosed via an‘other’or Unknown route.The proportion diagnosed via a TWW referral doubled between 2006-2017 rising from 9.9%to 19.8%,conversely EP diagnosis route declined,falling from 51.3%to 46.0%.Statistically significant variation in both the TWW referral and EP proportions was found across Cancer Alliances.Age,presence of comorbidity and underlying liver disease were independently associated with both a lower proportion of patients diagnosed via TWW referral,and a higher proportion diagnosed by EP after adjusting for other potential confounders.CONCLUSION There is significant geographic and socio-demographic variation in routes to diagnosis of CCA in England.Knowledge sharing of best practice may improve diagnostic pathways and reduce unwarranted variation.

Geographic Drone-based Route Optimization Approach for Emergency Area Ad-Hoc Network

Wireless sensor Mobile ad hoc networks have excellent potential in moving and monitoring disaster area networks on real-time basis.The recent challenges faced in Mobile Ad Hoc Networks(MANETs)include scalability,localization,heterogeneous network,self-organization,and self-sufficient operation.In this background,the current study focuses on specially-designed communication link establishment for high connection stability of wireless mobile sensor networks,especially in disaster area network.Existing protocols focus on location-dependent communications and use networks based on typically-used Internet Protocol(IP)architecture.However,IP-based communications have a few limitations such as inefficient bandwidth utilization,high processing,less transfer speeds,and excessive memory intake.To overcome these challenges,the number of neighbors(Node Density)is minimized and high Mobility Nodes(Node Speed)are avoided.The proposed Geographic Drone Based Route Optimization(GDRO)method reduces the entire overhead to a considerable level in an efficient manner and significantly improves the overall performance by identifying the disaster region.This drone communicates with anchor node periodically and shares the information to it so as to introduce a drone-based disaster network in an area.Geographic routing is a promising approach to enhance the routing efficiency in MANET.This algorithm helps in reaching the anchor(target)node with the help of Geographical Graph-Based Mapping(GGM).Global Positioning System(GPS)is enabled on mobile network of the anchor node which regularly broadcasts its location information that helps in finding the location.In first step,the node searches for local and remote anticipated Expected Transmission Count(ETX),thereby calculating the estimated distance.Received Signal Strength Indicator(RSSI)results are stored in the local memory of the node.Then,the node calculates the least remote anticipated ETX,Link Loss Rate,and information to the new location.Freeway Heuristic algorithm improves the data speed,efficiency and determines the path and optimization problem.In comparison with other models,the proposed method yielded an efficient communication,increased the throughput,and reduced the end-to-end delay,energy consumption and packet loss performance in disaster area networks.

Study on Rural Solid Waste Collection and Transportation Mode and Route Optimization Strategy in the Cold Regions of Northern China

Rural vitalization is a major strategy for reform and development of agriculture and rural areas in China,the key task of which is improving rural living environment.Imperfect rural solid waste(RSW)collection and transportation system exacerbates the pollution of RSW to rural living environment,while it has not been established and improved in the cold region of Northern China due to climate and economy.Through the analysis of the current situation of RSW source separation,collection,transportation and disposal in China,an RSW collection and transportation system suitable for the northern cold region was developed.Considering the low winter temperature in the northern cold region,different requirements for RSW collection,transportation and terminal disposal,scattered source points and single terminal disposal nodes in rural areas,the study focused on determining the number and location of transfer stations,established a model for transfer stations selection and RSW collection and transportation routes optimization for RSW collection and transportation system,and proposed the elite retention particle swarm optimization–genetic algorithm(ERPSO–GA).The rural area of Baiquan County was taken as a representative case,the collection and transportation scheme of which was given,and the feasibility of the scheme was clarified by simulation experiment.

Application Research of an Intelligent Detection Algorithm for Vehicle Trajectory Route Deviation

In the vehicle trajectory application system, it is often necessary to detect whether the vehicle deviates from the specified route. Trajectory planning in the traditional route deviation detection is defined by the driver through the mobile phone navigation software, which plays a more auxiliary driving role. This paper presents a method of vehicle trajectory deviation detection. Firstly, the manager customizes the trajectory planning and then uses big data technologies to match the deviation between the trajectory planning and the vehicle trajectory. Finally, it achieves the supervisory function of the manager on the vehicle track route in real-time. The results show that this method could detect the vehicle trajectory deviation quickly and accurately, and has practical application value.

Route Search Method for Railway Replacement Buses Adopting Ant Colony Optimization

In recent years, Japan, and especially rural areas have faced the growing problems of debt-ridden local railway lines along with the population decline and aging population. Therefore, it is best to consider the discontinuation of local railway lines and introduce replacement buses to secure the transportation methods of the local people especially in rural areas. Based on the above background, targeting local railway lines that may be discontinued in the near future, appropriate bus stops when provided with potential bus stops were selected, the present study proposed a method that introduces routes for railway replacement buses adopting ant colony optimization (ACO). The improved ACO was designed and developed based on the requirements set concerning the route length, number of turns, road width, accessibility of railway lines and zones without bus stops as well as the constraint conditions concerning the route length, number of turns and zones without bus stops. Original road network data were generated and processed adopting a geographic information systems (GIS), and these are used to search for the optimal route for railway replacement buses adopting the improved ACO concerning the 8 zones on the target railway line (JR Kakogawa line). By comparing the improved ACO with Dijkstra’s algorithm, its relevance was verified and areas needing further improvements were revealed.

Therapeutic Routes of a Group of Heart Failure Patients Followed in a Cameroonian Urban Setting

Background: Heart failure (HF) is a rising global health problem. Patients with HF tend to use several therapies obtained via different treatment routes to relieve their symptoms. It is rampant in sub-Saharan Africa (SSA), leading to poor health-seeking behaviours and worsened HF health outcomes. We aimed to describe the different therapeutic routes of HF patients from the onset of their first symptom until treatment in a specialised cardiology centre to identify and rebuke harmful therapeutic routes. Materials and Methods: This was a cross-sectional study at the Yaoundé Central Hospital in Cameroon between December 2018 to July 2019. Patients were recruited by consecutive convenient sampling. Adult patients aged above 18 years with confirmed HF were included using the Framingham criteria. Variables relating to socio-demographic and clinical data and the health-seeking behaviours of HF patients were studied. Results: We included 132 patients with a mean age of 62.90 years (62.88% women). Very few patients (0.90%) followed an ideal route;60.71% of subjects had a pseudo-ideal route, 19.64% accessed a specialised facility directly, and 21.42% used an erratic route. At the arrival time in a cardiology unit, 49.24% and 35.61% of our subjects were in NYHA stage III and IV HF compared to 15.15% for stage II. None of them was in Stage I. Conclusion: Most heart failure patients in Cameroon have resorted to non-specialised care, which worsens their clinical presentation. There is an urgent need for health education of HF patients in our context.

Design Strategies of Expressway Routes and Interchanges

Road traffic conditions can have an important impact on the economic development of various regions.Under the background of rapid social and economic development,more and more expressway construction projects are initiated in various regions,including both new expressways and expansion of old expressways,and interchange design plays an important role.Scientific and reasonable interchange design can not only realize energy saving and low carbon footprint,but also be people-oriented and promote regional economic development.Therefore,this paper mainly analyzes the highway route and its interchange design strategy for reference.

Fundamental Ideas and Basic Concepts of HSR Route Selection in Complicated Urban Areas

Up till now,no systematic studies on railway route selection in urban areas,HSR route selection in particular,have been taken in China.Based on the Shenzhen Railway Terminal Project and the Shenzhen-Shanwei Railway Project,research on HSR route selection in complicated urban areas has been conducted.An optimal route selection plan is determined after studying the local geological and environmental conditions and the complexity of tunnel construction.The research concludes that there are four major concerns in HSR route selection:the match between the new route and the urban planning,the potential economic return for the massive investment,the likely impacts of land expropriation on social stability,and the best synthesis of multiple controlling factors to meet the HSR standard.Moreover,six principles should be followed in railway route selection in complicated urban areas:the new route should be in alignment with the railway deployment;the route should align with the existing passage as much as possible;extensive analysis and in-depth demonstrations should be done to find the most appropriate combination of open and hidden excavation in tunnel construction;geological conditions and tunnel construction complexities are among the priorities;environmental sensitive sites and environmental vibration noise should be avoided as much as possible;special attention should be paid to the relocation of the power supply,television and communication facilities and the rearrangement of tubes and wires.