Academic literature on the topic 'AUTOMATED NUMBER'

This paper is a study on some upper bounds of the Mertens function, which is often considered somewhat of a ``mysterious" function in mathematics and is closely related to the Riemann Hypothesis. We discuss some known bounds of the Mertens function, and also seek new bounds with the help of an automated conjecture-making program named CONJECTURING, which was created by C. Larson and N. Van Cleemput, and inspired by Fajtowicz's Dalmatian Heuristic. By utilizing this powerful program, we were able to form, validate, and disprove hypotheses regarding the Mertens function and how it is bounded.

Intelligent Transportation Systems (ITSs) play an important role in modern traffic management, which can be divided into intelligent infrastructure systems and intelligent vehicle systems. Automatic Number Plate Recognition systems (ANPRs) are one of infrastructure systems that allow users to track, identify and monitor moving vehicles by automatically extracting their number plates. ANPR is a well proven technology that is widely used throughout the world by both public and commercial organisations. There are a wide variety of commercial uses for the technology that include automatic congestion charge systems, access control and tracing of stolen cars. The fundamental requirements of an ANPR system are image capture using an ANPR camera and processing of the captured image. The image processing part, which is a computationally intensive task, includes three stages: Number Plate Localisation (NPL), Character Segmentation (CS) and Optical Character Recognition (OCR). The common hardware choice for its implementation is often high performance workstations. However, the cost, compactness and power issues that come with these solutions motivate the search for other platforms. Recent improvements in low-power high-performance Field Programmable Gate Arrays (FPGAs) and Digital Signal Processors (DSPs) for image processing have motivated researchers to consider them as a low cost solution for accelerating such computationally intensive tasks. Current ANPR systems generally use a separate camera and a stand-alone computer for processing. By optimising the ANPR algorithms to take specific advantages of technical features and innovations available within new FPGAs, such as low power consumption, development time, and vast on-chip resources, it will be possible to replace the high performance roadside computers with small in-camera dedicated platforms. In spite of this, costs associated with the computational resources required for complex algorithms together with limited memory have hindered the development of embedded vision platforms. The work described in this thesis is concerned with the development of a range of image processing algorithms for NPL, CS and OCR and corresponding FPGA architectures. MATLAB implementations have been used as a proof of concept for the proposed algorithms prior to the hardware implementation. The proposed architectures are speed/area efficient architectures, which have been implemented and verified using the Mentor Graphics RC240 FPGA development board equipped with a 4M Gates Xilinx Virtex-4 LX40. The proposed NPL architecture can localise a number plate in 4.7 ms whilst achieving a 97.8% localisation rate and consuming only 33% of the available area of the Virtex-4 FPGA. The proposed CS architecture can segment the characters within a NP image in 0.2-1.4 ms with 97.7% successful segmentation rate and consumes only 11% of the Virtex-4 FPGA on-chip resources. The proposed OCR architecture can recognise a character in 0.7 ms with 97.3% successful recognition rate and consumes only 23% of the Virtex-4 FPGA available area. In addition to the three main stages, two pre-processing stages which consist of image binarisation, rotation and resizing are also proposed to link these stages together. These stages consume 9% of the available FPGA on-chip resources. The overall results achieved show that the entire ANPR system can be implemented on a single FPGA that can be placed within an ANPR camera housing to create a stand-alone unit. As the benefits of this are drastically improve energy efficiency and removing the need for the installation and cabling costs associated with bulky PCs situated in expensive, cooled, waterproof roadside cabinets.

In transport information area, in order to improve control system, identifying vehicle plates is very important. For that reason we are focusing on recognizing the vehicle plate from an image. To distinguish one car from others, one should remove all area except the vehicle plate. Due to the extra difficulties, like limited light, distances, moving etc., it can be hard to detect the final vehicle plate. In this work, we have solved the location of vehicle plate at night time, by separating the objects from the background by using morphological processing and analyzing the characteristics of vehicle plates by using removal of noise and mathematical calculations. According to some characteristics of cars and vehicle plates we developed an algorithm to detect the number of final vehicle plate. This algorithm works fine, and the detected result is accurate.

The thesis deals with the numbering plan, PBX, tariffs, draft disable tariff system and its possible extensions. Within numbering plans work deals with shapes of national and international figures, describes different types of these numbers, description of the structure and definition of fields, including the length of these fields. Within countries and regions of the Czech Republic are given individual prefix for both fixed and mobile networks. There are mentioned special shapes that are different in length compared to standard types. All these types of shapes are listed according to ITU-T. Within the exchanges are given generation switches, PBXs use within the telephone network and a description of the selected functions. Furthermore, there are kinds of pricing and options of valuation call. The work contains a description of automated acconting system, according to the principle of work of the program and a description of the individual steps and functions that thanks to the cooperation process individually each calls, convert numbers to international form, assigns the call tariff and appreciate the call according to the tariff. Finally, there are described possible extensions of this automated acconting system.

Ce travail de thèse traite de la modélisation et du contrôle des maladies infectieuses à l’aide des automates cellulaires. Nous nous sommes d’abord focalisés sur l’étude d’un modèle de type SEIR. Nous avons pu monter d’une part qu’un voisinage fixe pouvait entrainer une sous-évaluation de l’incidence et de la prévalence et d’autre part que sa structure a un impact direct sur la structure de la distribution de la maladie. Nous nous sommes intéressés également la propagation des maladies vectorielles à travers un modèle de type SIRS-SI multi-hôtes dans un environnement hétérogène.Les hôtes y étaient caractérisés par leur niveau de compétence et l’environnement par la variation du taux de reproduction et de mortalité. Son application à la maladie de Chagas, nous a permis de montrer que l’hétérogénéité de l’habitat et la diversité des hôtes contribuaient à faire baisser l’infection. Cependant l’un des principaux résultats de notre travail à été la formulation du nombre de reproduction spatiale grâce à deux matrices qui représentent les coefficients d’interactions entre les différentes cellules du réseau<br>This PhD thesis considers the general problem of epidemiological modelling and control using cellular automata approach.We first focused on the study of the SEIR model. On the one hand, we have shown that the traditionnal neighborhood contribute to underestimate the incidence and prevalence of infection disease. On the other hand, it appeared that the spatial distribution of the cells in the lattice have a real impact on the disease spreading. The second study concerns the transmission of the vector-borne disease in heterogeneous landscape with host community. We considered a SIRS-SI with various level of competence at witch the environnment heterogeneity has been characterized by the variation of the birth flow and the death rate. We simulated the Chagas disease spreading and shown that the heterogeneity of habitat and host diversity contribute to decrease the infection. One of the most important results of our work, was the proposition of the spatial reproduction number expression based on two matrices that represent the interaction factors between the cells in the lattice

Number of lanes is a basic roadway attribute that is widely used in many transportation applications. Traditionally, number of lanes is collected and updated through field surveys, which is expensive especially for large coverage areas with a high volume of road segments. One alternative is through manual data extraction from high-resolution aerial images. However, this is feasible only for smaller areas. For large areas that may involve tens of thousands of aerial images and millions of road segments, an automatic extraction is a more feasible approach. This dissertation aims to improve the existing process of extracting number of lanes from aerial images automatically by making improvements in three specific areas: (1) performance of lane model, (2) automatic acquisition of external knowledge, and (3) automatic lane location identification and reliability estimation. In this dissertation, a framework was developed to automatically recognize and extract number of lanes from geo-rectified aerial images. In order to address the external knowledge acquisition problem in this framework, a mapping technique was developed to automatically estimate the approximate pixel locations of road segments and the travel direction of the target roads in aerial images. A lane model was developed based on the typical appearance features of travel lanes in color aerial images. It provides more resistance to “noise” such as presence of vehicle occlusions and sidewalks. Multi-class classification test results based on the K-nearest neighbor, logistic regression, and Support Vector Machine (SVM) classification algorithms showed that the new model provides a high level of prediction accuracy. Two optimization algorithms based on fixed and flexible lane widths, respectively, were then developed to extract number of lanes from the lane model output. The flexible lane-width approach was recommended because it solved the problems of error-tolerant pixel mapping and reliability estimation. The approach was tested using a lane model with two SVM classifiers, i.e., the Polynomial kernel and the Radial Basis Function (RBF) kernel. The results showed that the framework yielded good performance in a general test scenario with mixed types of road segments and another test scenario with heavy plant occlusions.

Traditional manual survey methods for collecting reliable origin-destination data to develop large strategic transport model is notoriously expensive and the sample sizes are often relatively small. Arguably, the least reliable data required for the development of strategic traffic models is the origin-destination data. Recent technological advances, such as probe data from on-board devices, have been successful in providing data for some needs such as journey times and routing options. However, varying degrees of success have been achieved in obtaining reliable origin-destination (OD) data from these new technologies. Automatic Number Plate Recognition (ANPR) is one if the newer technologies that could be used to collect large-scale data sets over the large study areas that strategic traffic models cover. The aim of this study is to examine ANPR data collected from the Gauteng Freeway Improvement Project's (GFIP) Open Road Tolling (ORT) gantries in terms of its accuracy and uses in the development and improvement of strategic traffic models. Of particular interest is the use of the ANPR data to contribute towards the improvement of the distribution of trips in the OD matrices. This is achieved by developing methodologies to derive comparable gantry to gantry traffic volumes from the ANPR data and the GFIP traffic model. The above comparisons enabled the undertaking of a post opening project evaluation of the GFIP traffic model's 2015 forecasts using as many characteristics of the traffic flows and patterns that can be derived from the ANPR data. Characteristics such as traffic volumes and journey times are directly comparable with standard traffic model outputs. Tracking vehicles between gantries enabled the calculation of the number of trips that travel between gantry pairs giving rise to gantry-to-gantry (G2G) trips, which can be represented in a G2G count matrix. This G2G count matrix has probably the most beneficial data that can be derived from the ANPR systems as it contains an "accurate" element of the trip distribution on the road network. A methodology was developed to derive equivalent trip matrices from a traffic model's select-link trip matrices where the links are those where the gantry (ANPR camera) is located. The sums of the trips in the derived sub-matrices match the G2G counts. This enabled the comparison between the modelled trip distribution represented by the select link to select link (SL2SL) volumes and the actual ANPR G2G counts. This is in fact a comparison of a portion of the model's distribution to actual, comprehensive data. This study demonstrates that ANPR data has the potential to improve strategic traffic models. The automation of the processes to derive the SL2SL assigned volumes from the models and combining it with existing matrix estimation techniques will enhance the trip distribution in the output trip matrix. The current practice of using individual traffic counts in matrix estimation has the adverse tendency to affect the trip distribution. Hence, the recommendation to use traffic counts in matrix estimation to traffic counts with caution.<br>Dissertation (MEng)--University of Pretoria, 2017.<br>Civil Engineering<br>MEng<br>Unrestricted