The multilevel trigger system of the DIRAC experiment

The multilevel trigger system of the DIRAC experiment at CERN is presented. It includes a fast first level trigger as well as various trigger processors to select events with a pair of pions having a low relative momentum typical of the physical process under study. One of these processors employs the drift chamber data, another one is based on a neural network algorithm and the others use various hit-map detector correlations. Two versions of the trigger system used at different stages of the experiment are described. The complete system reduces the event rate by a factor of 1000, with efficiency $\geq$95% of detecting the events in the relative momentum range of interest.Comment: 21 pages, 11 figure

Jet production measurements at CMS

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Low cost vision based personal mobile mapping system

Mobile mapping systems (MMS) can be used for several purposes, such as transportation, highway infrastructure mapping and GIS data collecting. However, the acceptance of these systems is not wide spread and their use is still limited due the high cost and dependency on the Global Navigation Satellite System (GNSS). A low cost vision based personal MMS has been produced with an aim to overcome these limitations. The system has been designed to depend mainly on cameras and use of low cost GNSS and inertial sensors to provide a bundle adjustment solution with initial values. The system has the potential to be used indoor and outdoor. The system has been tested indoors and outdoors with different GPS coverage, surrounded features, and narrow and curvy paths. Tests show that the system is able to work in such environments providing 3D coordinates of better than 10 cm accuracy

A compact plug-in module for LHC-like trigger emulation

A compact trigger emulation module for evaluating electronic systems for LHC applications has been built using off-the-shelf components. The emulator, which is based on an FPGA, generates both programmable and true-random trigger patterns in compliance with the LHC triggering rules. For the true-random trigger part, the source of randomness is the avalanche effect on a transistor emitter-base diode. The system can be used either as a plug-in module for VME systems or as a standalone device controlled via a standard USB link by a PC running LabVIEW

Monitoring deformation of small scale model tunnels under load testing

This paper describes a study to assess the suitability of two non-contact methods of measurement used to monitor a series of small scale model tunnels built to different specifications that are being subjected to load testing. The model tunnels are being built to validate mathematical modelling techniques. Presented here are the results to assess the suitability and quality of survey results based on photogrammetry and laser scanning. The two key parameters to be measured are the deformation that is created in the tunnel (distance measurement) and the length and width of cracks. Results showed that both the remote measurement techniques were suitable for the measurement of the small model tunnels and compared well against appropriate potentiometer and vernier calliper measurements

An approach to produce a GIS database for road surface monitoring

Road Surface Monitoring (RSM) is the process of detecting the distress on paved or unpaved road surfaces. The primary aim of this process is to detect any distress (such as road surface cracks) at early stages in order to apply maintenance on time. Early detection of road cracks can assist maintenance before the repair costs becomes too high. Local authorities should have an effective and easy to use monitoring process in place across the road network to meet their obligations. The process of adding geographical identification metadata to the photos is called “Geo-tagging”. The proposed method in this work entails capturing GPS information when the photo is taken for the road surface distress, then attaching the photo to a map. The location disclosure in the act of geo-tagging of a photo provides qualities to the digital map. In that respect, a specific richness of the GIS dataset arises when they disclose the road surface distress photos. This paper proposes a system for establishing a GIS database consisting of geo-tagged photos for local authorities to automate the process of recording and reporting road surface distresses. This system is easy to use, cost-effective, deployable, and can be used effectively by local authorities

An investigation into semi-automated 3D city modelling

Creating three dimensional digital representations of urban areas, also known as 3D city modelling, is essential in many applications, such as urban planning, radio frequency signal propagation, flight simulation and vehicle navigation, which are of increasing importance in modern society urban centres. The main aim of the thesis is the development of a semi-automated, innovative workflow for creating 3D city models using aerial photographs and LiDAR data collected from various airborne sensors. The complexity of this aim necessitates the development of an efficient and reliable way to progress from manually intensive operations to an increased level of automation. The proposed methodology exploits the combination of different datasets, also known as data fusion, to achieve reliable results in different study areas. Data fusion techniques are used to combine linear features, extracted from aerial photographs, with either LiDAR data or any other source available including Very Dense Digital Surface Models (VDDSMs). The research proposes a method which employs a semi automated technique for 3D city modelling by fusing LiDAR if available or VDDSMs with 3D linear features extracted from stereo pairs of photographs. The building detection and the generation of the building footprint is performed with the use of a plane fitting algorithm on the LiDAR or VDDSMs using conditions based on the slope of the roofs and the minimum size of the buildings. The initial building footprint is subsequently generalized using a simplification algorithm that enhances the orthogonality between the individual linear segments within a defined tolerance. The final refinement of the building outline is performed for each linear segment using the filtered stereo matched points with a least squares estimation. The digital reconstruction of the roof shapes is performed by implementing a least squares-plane fitting algorithm on the classified VDDSMs, which is restricted by the building outlines, the minimum size of the planes and the maximum height tolerance between adjacent 3D points. Subsequently neighbouring planes are merged using Boolean operations for generation of solid features. The results indicate very detailed building models. Various roof details such as dormers and chimneys are successfully reconstructed in most cases

Implementation of On-Line Data Reduction Algorithms in the CMS Endcap Preshower Data Concentrator Card

The CMS Endcap Preshower (ES) sub-detector comprises 4288 silicon sensors, each containing 32 strips. The data are transferred from the detector to the counting room via 1208 optical fibres running at 800Mbps. Each fibre carries data from 2, 3 or 4 sensors. For the readout of the Preshower, a VME-based system - the Endcap Preshower Data Concentrator Card (ES-DCC) is currently under development. The main objective of each readout board is to acquire on-detector data from up to 36 optical links, perform on-line data reduction (zero suppression) and pass the concentrated data to the CMS event builder. This document presents the conceptual design of the Reduction Algorithms as well as their implementation into the ES-DCC FPGAs. The algorithms implemented into the ES-DCC resulted in a reduction factor of ~20

An investigation into semi-automated 3D city modelling

Creating three dimensional digital representations of urban areas, also known as 3D city modelling, is essential in many applications, such as urban planning, radio frequency signal propagation, flight simulation and vehicle navigation, which are of increasing importance in modern society urban centres. The main aim of the thesis is the development of a semi-automated, innovative workflow for creating 3D city models using aerial photographs and LiDAR data collected from various airborne sensors. The complexity of this aim necessitates the development of an efficient and reliable way to progress from manually intensive operations to an increased level of automation. The proposed methodology exploits the combination of different datasets, also known as data fusion, to achieve reliable results in different study areas. Data fusion techniques are used to combine linear features, extracted from aerial photographs, with either LiDAR data or any other source available including Very Dense Digital Surface Models (VDDSMs). The research proposes a method which employs a semi automated technique for 3D city modelling by fusing LiDAR if available or VDDSMs with 3D linear features extracted from stereo pairs of photographs. The building detection and the generation of the building footprint is performed with the use of a plane fitting algorithm on the LiDAR or VDDSMs using conditions based on the slope of the roofs and the minimum size of the buildings. The initial building footprint is subsequently generalized using a simplification algorithm that enhances the orthogonality between the individual linear segments within a defined tolerance. The final refinement of the building outline is performed for each linear segment using the filtered stereo matched points with a least squares estimation. The digital reconstruction of the roof shapes is performed by implementing a least squares-plane fitting algorithm on the classified VDDSMs, which is restricted by the building outlines, the minimum size of the planes and the maximum height tolerance between adjacent 3D points. Subsequently neighbouring planes are merged using Boolean operations for generation of solid features. The results indicate very detailed building models. Various roof details such as dormers and chimneys are successfully reconstructed in most cases