Methods and apparatuses are disclosed herein for population tracking, counting and/or movement estimation. In one embodiment, the method comprises receiving mobile phone operational data indicative of user equipment location, where the event data includes location area update messages and periodic registration messages; and performing travel estimation based on the mobile phone operation data, including performing interpolation on data associated with one or more individuals in a population to estimate intermediate positions of a trajectory of each of the one or more individuals for a specified time period based on a shortest path mesh sequence estimation algorithm.

System and method for population tracking, counting, and movement estimation using mobile operational data and/or geographic information in mobile network

This paper reviews Dijkstra Algorithm implementation in finding the shortest path for route planning. The regular shortest path algorithms do not consider the timebase dynamic traffic condition of road network, i.e the hourly changing of traffic density. Timebase dynamic weight for Dijkstra Algorithm compute the most efficient time and minimum fuel consumption based on the real condition of the traffic profiles of the road network. The traffic profiles describe the time needed to pass the road based on time which also differs for workdays and weekend. Simulation shows the implementation of Timebase Dynamic Weight for Dijkstra Algorithm can give better cost efficiency compared with the common Shortest Distance calculation and Traffic Avoidance calculation.

Timebase dynamic weight for Dijkstra Algorithm implementation in route planning software

http://www.cs.bilkent.edu.tr/tech-reports/2007/BU-CE-0707.pdf

A link-based storage scheme for efficient aggregate query processing on clustered road networks

Sustainable development and flood risk management

Of late, component based software design has become a major focus in software engineering research and computing practice. These software components are used in a wide range of applications some of which may have mission critical requirements. In order to achieve required level of reliability, these component-based designs have to incorporate special measures to cope up with software faults. This paper presents a fault tolerant component based data driven architecture that is based on C2 architectural framework and implements data diverse fault tolerance strategies. The proposed design makes a trade-off between platform flexibility, reliability and efficiency at run time and exhibits its ability to tolerate faults in a cost effective manner. Application of proposed design is exhibited with a case study.

Data diverse fault tolerant architecture for component based systems

Traditional shortest path algorithm didn't consider the condition of road network, such as no left-turn. This paper restructured the topology of network chart considering the complex traffic regulations, in order to rebuild the model of urban traffic network, and proposed a new optimal path algorithm adapted for urban traffic guidance system based on Dijkstra algorithm. At last, we used Visual Basic and MapX control to implement the optimal algorithm in Geography Information System (GIS).

Research and Realization of the Optimal Path Algorithm with Complex Traffic Regulations in GIS

Dynamically updated and fine‐grained flooding maps are critical for situational awareness and decision support. However, traditional methods, such as eyewitness reports, remote sensing, and hydrology models, may fail to correspond with the rapidly changing urban hydrological environment. The presence of crowdsourced data (such as social media data) allows for timely and cost‐effective monitoring of flood hazards through collective observations; however, such data can be unreliable due to sample bias and low spatiotemporal resolution. Therefore, new measures to identify flood‐affected roads are desirable. In this study, we propose a methodology that leverages taxi GPS data to support post‐event flood mapping for the road network. This method can identify whether a significant reduction in the taxi passing rate for a road segment was related to precipitation, and automatically recognize the flood‐affected roads based on a logistic regression model. Using taxi GPS data in Shenzhen as an example, we derived the flood map of the road networks, and compared and validated the results. This study demonstrated the usefulness of taxi GPS data in generating high‐quality flood maps and the value of incorporating multiple data sources for sensing near real‐time flood in the city.

Post‐event flood mapping for road networks using taxi GPS data

The proportion of insulators in aerial power patrol images is small and the background of overhead lines is complex, often leading to incomplete and inaccurate detection of insulators. Therefore, an algorithm for detecting insulator targets based on multi-feature fusion is developed in this study. Firstly, a dynamic threshold oriented fast and rotated brief algorithm is proposed, which uses the bag-of-words dictionary model to determine local shape features of the image, applies gradient weighting to the global texture feature vector extracted by the histogram of oriented gradients algorithm and performs radial gradient transformations to get the improved HOG of features. Secondly, the feature vectors are fused serially, the learning machine is trained and the parameters of the support vector machine are optimized using the quantum particle swarm optimization algorithm. Finally, the target area is pre-divided by the selective search algorithm, and the area is classified by the learning machine. The experimental results show that the proposed feature extraction method can describe the image details more accurately than the existing methods, and the average accuracy of the feature extraction classifier can reach 93.7%, which helps to overcome the incomplete detection problem of insulator detection at the aerial work site. 

https://onlinelibrary.wiley.com/doi/pdfdirect/10.1049/ipr2.12735

Small insulator target detection based on multi-feature fusion

As an important department of railway transportation and production, large freight train depot is responsible for the regular overhaul and maintenance of railway trucks. The shunting operation of freight train depot covers the whole process of railway trucks entering, storing, overhauling and leaving the depot. It is an important step in the implemen-tation of the maintenance operation. Usually, shunting personnel in the depot transport the trucks to be overhauled to the maintenance line by relying on the shunting operation plan, which is the key to determine the shunting operation plan according to the distribution relationship between vehicles and maintenance. Firstly, this paper analyzes the process of centralized shunting operation in the freight train depot and the factors affecting the time-consuming based on the research idea of flexible workshop scheduling problem. Then, on the premise that the proportion of the weight coefficient will have an impact on the time-consuming of truck busy and shunting in the shunting process, and with the goal of minimizing the time-consuming of truck maintenance busy and shunting, the allocation model between trucks and maintenance lines is established; In addition, an improved genetic algorithm is proposed to solve the established model; Finally, combined with the maintenance of railway trucks in a large freight train depot, an example analysis is carried out on this basis. The results demonstrate that using simulated annealing genetic algorithm to solve the model can obtain the allocation scheme between railway trucks and maintenance operation line. Under the influence of three different coefficients, compared with genetic algorithm, simulated annealing genetic algorithm can reduce the deten-tion time of railway trucks in depot by 0.21%, 0.09% and 0.12% respectively, which is beneficial to reducing the deten-tion time of maintenance vehicles in depot, It plays a positive role in improving the maintenance efficiency of trucks in the depot, and also provides new ideas for the research of railway truck shunting operation.



Determination of Truck Maintenance Allocation Scheme Based on SA-GA

Aiming at the problem of serious manual intervention, poor adaptive ability, and gradient calculation’s low accuracy of Canny algorithm in filtering and threshold detection. An improved edge detection algorithm is put forward based on Canny. Firstly, adaptive smoothing filtering method is used to reduce sensitivity to noise. Secondly, accuracy of edge detection is improved by calculating gradient amplitude in eight directional templates. And non-maximum suppression is used to eliminate invalid pixels. Finally, an improved threshold detection algorithm is adopted to improve the uncertainty of manual threshold selection and improve the accuracy of edge detection. In terms of detection, three parameters including Structural Similarity Index Metric (SSIM), Mean Squared Error (MSE) and Peak Signal to Noise Ration (PSNR) are used to evaluate the similarity of classic images, then the wheelset tread damage problem of high speed trains is analyzed as practical engineering application. The experimental results show that under the condition of 15% salt and pepper noise, after denoising, SSIM of the image is improved by 5.3192%, MSE is improved by 4.6887%, and PSNR is improved by 0.6216%. The following conclusions are drawn: the algorithm proposed this study is optimized based on Canny algorithm, which can effectively suppress salt and pepper noise, reduce the appearance of false edges, and the image edge details are more completed after processing.

Jiandong Qiu

Papers

Research and Realization of the Optimal Path Algorithm with Complex Traffic Regulations in GIS

Post‐event flood mapping for road networks using taxi GPS data

Small insulator target detection based on multi-feature fusion

Determination of Truck Maintenance Allocation Scheme Based on SA-GA

The edge detection optimization considering existing problems of Canny algorithm