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Recently, the number of high-resolution Earth-observing satellite sensors has been increasing owing to the growing needs of intelligence, mapping, and environmental monitoring. An acquired satellite image should be processed for analysis-ready data (ARD) that can be used for many applications. An important step among the processing is georeferencing that assigns geographic coordinates to each image pixel. These days, georeferencing is directly carried out using onboard sensors to produce sensor model information such as rational polynomial coefficients (RPCs). However, postprocessing is required to increase the positional accuracy of RPCs through bias compensation. Recently, bias compensation has been carried out on the basis of an automated process using ground control point (GCP) image chips. Image matching is carried out between the chips and the target satellite image to model the bias over the entire image. However, if the dissimilarity between the chip and the target satellite image increases owing to large differences in acquisition time and seasonal differences, the image matching often fails. Therefore, in this study, we utilized both intensity-based matching and edge-based matching to overcome these issues. We selected normalized cross-correlation (NCC) for intensity-based matching and relative edge cross-correlation (RECC) for edge-based matching. First, GCP chips were projected onto the target satellite images to align the two datasets. Then, both image matching methods were carried out in a pyramid image matching scheme, and their results were merged before RPC bias compensation with outlier removal. The experiments were carried out for two Kompsat-3A strips consisting of 9 and 7 scenes. NCC and RECC showed different matching results per scene, but RECC tended to show better results. NCC + RECC could derive most matching points, but the accuracy was between NCC and RECC. However, NCC + RECC shows potential to suppress a matching outlier. By applying automated bias compensation, 1.1-1.2 pixels of accuracy in root mean square error (RMSE) could be obtained. [ABSTRACT FROM AUTHOR]

The vast potential of high-resolution satellite images, including Kompsat-3A, has been demonstrated across diverse applications, such as mapping and disaster monitoring. However, these images can only be utilized as reliable GIS (geographic information system) data when they possess precise geographical information. To achieve this, sensor model information, represented by RPCs (rational polynomial coefficients), requires bias compensation through GCPs (ground control points). Though having a substantial number of well-distributed GCPs across satellite images is ideal, the acquisition process is often restricted due to cost and inaccessibility. The uniform distribution of GCP chips is not guaranteed, necessitating an investigation into the impact of GCP distribution on the bias compensation process, which is the focus of this study. Experiments were meticulously conducted using Kompsat-3A data using dense GCP information. The dense GCP information was automatically generated from aerial orthoimages through a three-step process. Firstly, the GCP chips were extracted from the aerial images, focusing on feature points. Secondly, these chips were projected onto the target Kompsat-3A data to align them accurately. Lastly, precise satellite image coordinates of the chips were obtained through image matching between the chips and the target Kompsat-3A image. The dense GCPs enabled detailed bias analysis that exhibited skewness in most Kompsat-3A data. This necessitates the implementation of an affine model for proper bias compensation over the entire image space. Next, the study delved into the influence of GCP distribution on RPC bias compensation. To this end, each target satellite image space was divided into nine zones, with the dense GCPs assigned accordingly. The accuracy of bias compensation was analyzed across nine experimental cases, ranging from GCPs occupying only one zone to GCPs covering all nine zones. It was observed that GCPs covering at least four or five zones should be utilized for reliable RPC bias compensation of Kompsat-3A, especially when aiming for a high level of accuracy with an RMSE of one pixel. Finally, it was concluded that GCPs covering three zones yielded satisfactory results as a minimum GCP requirement, but this was contingent upon their distribution not following a straight zone pattern. [ABSTRACT FROM AUTHOR]

The vast potential of high-resolution satellite images, including Kompsat-3A, has been demonstrated across diverse applications, such as mapping and disaster monitoring. However, these images can only be utilized as reliable GIS (geographic information system) data when they possess precise geographical information. To achieve this, sensor model information, represented by RPCs (rational polynomial coefficients), requires bias compensation through GCPs (ground control points). Though having a substantial number of well-distributed GCPs across satellite images is ideal, the acquisition process is often restricted due to cost and inaccessibility. The uniform distribution of GCP chips is not guaranteed, necessitating an investigation into the impact of GCP distribution on the bias compensation process, which is the focus of this study. Experiments were meticulously conducted using Kompsat-3A data using dense GCP information. The dense GCP information was automatically generated from aerial orthoimages through a three-step process. Firstly, the GCP chips were extracted from the aerial images, focusing on feature points. Secondly, these chips were projected onto the target Kompsat-3A data to align them accurately. Lastly, precise satellite image coordinates of the chips were obtained through image matching between the chips and the target Kompsat-3A image. The dense GCPs enabled detailed bias analysis that exhibited skewness in most Kompsat-3A data. This necessitates the implementation of an affine model for proper bias compensation over the entire image space. Next, the study delved into the influence of GCP distribution on RPC bias compensation. To this end, each target satellite image space was divided into nine zones, with the dense GCPs assigned accordingly. The accuracy of bias compensation was analyzed across nine experimental cases, ranging from GCPs occupying only one zone to GCPs covering all nine zones. It was observed that GCPs covering at least four or five zones should be utilized for reliable RPC bias compensation of Kompsat-3A, especially when aiming for a high level of accuracy with an RMSE of one pixel. Finally, it was concluded that GCPs covering three zones yielded satisfactory results as a minimum GCP requirement, but this was contingent upon their distribution not following a straight zone pattern.

Many high-resolution satellite images are acquired in the strip mode, in which the imaging direction is aligned with the satellite trajectory. A long strip image is often sliced into several scenes before delivery, and customers preprocess each scene with auxiliary data before their applications. Sensor model information is often provided for each scene in the form of rational polynomial coefficients (RPCs). The original RPCs of each scene are erroneous, and should be bias-compensated using ground reference data or ground control points. In this study, we propose the use of single RPCs for long image strips. However, a simple replacement of the physical sensor model using RPCs for the entire strip may cause large errors, because RPCs do not model large satellite attitude changes. Therefore, we applied the fitting of the satellite attitude to a linear equation before RPCs generation for a long-strip image. The test was conducted for three Kompsat-3A image strips consisting of multiple scenes, where one strip shows large satellite attitude changes. From the experiments, the RPCs generated for the whole image strip showed large errors compared to the strip adjustment; however, the proposed method could reduce the errors to an accuracy comparable to that of scene-based RPCs. [ABSTRACT FROM AUTHOR]

A CAS500-1 (Compact Advanced Satellite) is a high-resolution Earth-observing satellite launched in Mar 2021 and being operated by National Land Satellite Center at NGII (National Geographic Information Institute). The mission of the satellite is the periodic monitoring of the land for efficient managements. Having completed the calibration and validation processes, CAS500-1 has been acquiring land images to generate the basic geospatial information that are topographic maps, orthorectified images, and DEM (Digital Elevation Model). Using satellite data has a lot of advantages over aerial images in terms of repeatability, coverage, and accessibility. However, the spatial resolution is relatively lower than that of aerial images. This prohibits the large scale topographic mapping from the satellite data. Therefore, we conducted 1:5,000 large scale topographic mappings using CAS500-1 stereo data and assessed the accuracy. Two test areas were selected including accessible and inaccessible areas. Overlapping CAS500-1 data were automatically processed with GCP (Ground Control Points) chips for better positional accuracy. Then they are used for the epipolar resampled images that can be used for stereo-plotting. Through the stereo display quality assessment, we selected the optimal stereo set for each site. The accuracy of the resulted topographic maps was checked using ground truth data such as GNSS (Global Navigation Satellite System)-surveyed points over the accessible area and GCP chips in the inaccessible area, respectively. The experimental results showed the accuracy successfully met the requirement of 1:5,000 topographic map in Korea. We concluded that CAS500-1 data will have more potential for large scale mapping considering that CAS500-2 is scheduled to be launched in 2022 and cooperate with CAS500-1. [ABSTRACT FROM AUTHOR]

Featured Application: The proposed method can generate a mosaic image at the product level that is corrected only for radiometric and sensor distortions. High-resolution satellite images such as KOMPSAT-3 data provide detailed geospatial information over interest areas that are evenly located in an inaccessible area. The high-resolution satellite cameras are designed with a long focal length and a narrow field of view to increase spatial resolution. Thus, images show relatively narrow swath widths (10–15 km) compared to dozens or hundreds of kilometers in mid-/low-resolution satellite data. Therefore, users often face obstacles to orthorectify and mosaic a bundle of delivered images to create a complete image map. With a single mosaicked image at the sensor level delivered only with radiometric correction, users can process and manage simplified data more efficiently. Thus, we propose sensor-level mosaicking to generate a seamless image product with geometric accuracy to meet mapping requirements. Among adjacent image data with some overlaps, one image is the reference, whereas the others are projected using the sensor model information with shuttle radar topography mission. In the overlapped area, the geometric discrepancy between the data is modeled in spline along the image line based on image matching with outlier removals. The new sensor model information for the mosaicked image is generated by extending that of the reference image. Three strips of KOMPSAT-3 data were tested for the experiment. The data showed that irregular image discrepancies between the adjacent data were observed along the image line. This indicated that the proposed method successfully identified and removed these discrepancies. Additionally, sensor modeling information of the resulted mosaic could be improved by using the averaging effects of input data. [ABSTRACT FROM AUTHOR]

Extensible modalities and Web services have garnered significant interest from both biologists and cyberneticists in the last several years. Our objective here is to set the record straight and confirm the development of super pages. The properties of our approach depend greatly on the assumptions inherent in our model is Von Neumann machines. In fact, the main contribution of our work is that we constructed new robust technology (Von Neumann machines), showing that multicast systems and congestion control can collaborate to surmount this quandary. Von Neumann machines that are supported with Apple newtons are independently more effective In the end, we proposed a novel framework for the improvement of the UNIVAC computer (Von Neumann machines), which we used to argue that A* search and write-back caches can collude to fulfill this aim. [ABSTRACT FROM AUTHOR]

Epipolar images can improve the efficiency and accuracy of dense matching by restricting the search range of correspondences from 2-D to 1-D, which play an important role in 3-D reconstruction. As most of the satellite images in archives are incidental collections, which do not have rigorous stereo properties, in this paper, we propose a general framework to generate epipolar images for both in-track and cross-track stereo images. We first investigate the theoretical epipolar constraints of single-sensor and multi-sensor images and then introduce the proposed framework in detail. Considering large elevation changes in mountain areas, the publicly available digital elevation model (DEM) is applied to reduce the initial offsets of two stereo images. The left image is projected into the image coordinate system of the right image using the rational polynomial coefficients (RPCs). By dividing the raw images into several blocks, the epipolar images of each block are parallel generated through a robust feature matching method and fundamental matrix estimation, in which way, the horizontal disparity can be drastically reduced while maintaining negligible vertical disparity for epipolar blocks. Then, stereo matching using the epipolar blocks can be easily implemented and the forward intersection method is used to generate the digital surface model (DSM). Experimental results on several in-track and cross-track images, including optical-optical, SAR-SAR, and SAR-optical pairs, demonstrate the effectiveness of the proposed framework, which not only has obvious advantages in mountain areas with large elevation changes but also can generate high-quality epipolar images for flat areas. The generated epipolar images of a ZiYuan-3 pair in Songshan are further utilized to produce a high-precision DSM.

High-resolution satellite images such as KOMPSAT-3 data provide detailed geospatial information over interest areas that are evenly located in an inaccessible area. The high-resolution satellite cameras are designed with a long focal length and a narrow field of view to increase spatial resolution. Thus, images show relatively narrow swath widths (10–15 km) compared to dozens or hundreds of kilometers in mid-/low-resolution satellite data. Therefore, users often face obstacles to orthorectify and mosaic a bundle of delivered images to create a complete image map. With a single mosaicked image at the sensor level delivered only with radiometric correction, users can process and manage simplified data more efficiently. Thus, we propose sensor-level mosaicking to generate a seamless image product with geometric accuracy to meet mapping requirements. Among adjacent image data with some overlaps, one image is the reference, whereas the others are projected using the sensor model information with shuttle radar topography mission. In the overlapped area, the geometric discrepancy between the data is modeled in spline along the image line based on image matching with outlier removals. The new sensor model information for the mosaicked image is generated by extending that of the reference image. Three strips of KOMPSAT-3 data were tested for the experiment. The data showed that irregular image discrepancies between the adjacent data were observed along the image line. This indicated that the proposed method successfully identified and removed these discrepancies. Additionally, sensor modeling information of the resulted mosaic could be improved by using the averaging effects of input data.

Synthesis of renin in renal renin-producing cells (RPCs) is controlled via the intracellular messenger cAMP. Interference with cAMP-mediated signaling by inducible knockout of Gs-alpha (Gsα) in RPCs of adult mice resulted in a complex adverse kidney phenotype. Therein, glomerular endothelial damage was most striking. In this study, we investigated whether Gsα knockout leads to a loss of RPCs, which itself may contribute to the endothelial injury. We compared the kidney phenotype of three RPC-specific conditional mouse lines during continuous induction of recombination. Mice expressing red fluorescent reporter protein tdTomato (tdT) in RPCs served as controls. tdT was also expressed in RPCs of the other two strains used, namely with RPC-specific Gsα knockout (Gsα mice) or with RPC-specific diphtheria toxin A expression (DTA mice, in which the RPCs should be diminished). Using immunohistological analysis, we found that RPCs decreased by 82% in the kidneys of Gsα mice as compared with controls. However, the number of tdT-positive cells was similar in the two strains, demonstrating that after Gsα knockout, the RPCs persist as renin-negative descendants. In contrast, both renin-positive and tdT-labeled cells decreased by 80% in DTA mice suggesting effective RPC ablation. Only Gsα mice displayed dysregulated endothelial cell marker expression indicating glomerular endothelial damage. In addition, a robust induction of genes involved in tissue remodelling with microvascular damage was identified in tdT-labeled RPCs isolated from Gsα mice. We concluded that Gsα/renin double-negative RPC progeny essentially contributes for the development of glomerular endothelial damage in our Gsα-deficient mice. [ABSTRACT FROM AUTHOR]

Kompsat-3/3A provides along-track and across-track stereo data for accurate three-dimensional (3D) topographic mapping. Stereo data preprocessing involves conjugate point extraction and acquisition of ground control points (GCPs), rational polynomial coefficient (RPC) bias compensation, and epipolar image resampling. Applications where absolute positional accuracy is not a top priority do not require GCPs, but require precise conjugate points from stereo images for subsequent RPC bias compensation, i.e., relative orientation. Conjugate points are extracted between the original stereo data using image-matching methods by a proper outlier removal process. Inaccurate matching results and potential outliers produce geometric inconsistency in the stereo data. Hence, the reliability of conjugate point extraction must be improved. For this purpose, we proposed to apply the coarse epipolar resampling using raw RPCs before the conjugate point matching. We expect epipolar images with even inaccurate RPCs to show better stereo similarity than the original images, providing better conjugate point extraction. To this end, we carried out the quantitative analysis of the conjugate point extraction performance by comparing the proposed approach using the coarsely epipolar resampled images to the traditional approach using the original stereo images. We tested along-track Kompsat-3 stereo and across-track Kompsat-3A stereo data with four well-known image-matching methods: phase correlation (PC), mutual information (MI), speeded up robust features (SURF), and Harris detector combined with fast retina keypoint (FREAK) descriptor (i.e., Harris). These matching methods were applied to the original stereo images and coarsely resampled epipolar images, and the conjugate point extraction performance was investigated. Experimental results showed that the coarse epipolar image approach was very helpful for accurate conjugate point extraction, realizing highly accurate RPC refinement and sub-pixel y-parallax through fine epipolar image resampling, which was not achievable through the traditional approach. MI and PC provided the most stable results for both along-track and across-track test data with larger patch sizes of more than 400 pixels.

Photogrammetry is currently in a process of renaissance, caused by the development of dense stereo matching algorithms to provide very dense Digital Surface Models (DSMs). Moreover, satellite sensors have improved to provide sub-meter or even better Ground Sampling Distances (GSD) in recent years. Therefore, the generation of DSM from spaceborne stereo imagery becomes a vivid research area. This paper presents a comprehensive study about the DSM generation of high resolution satellite data and proposes several methods to implement the approach. The bias-compensated Rational Polynomial Coefficients (RPCs) Bundle Block Adjustment is applied to image orientation and the rectification of stereo scenes is realized based on the Project-Trajectory-Based Epipolarity (PTE) Model. Very dense DSMs are generated from WorldView-2 satellite stereo imagery using the dense image matching module of the C/C++ library LibTsgm. We carry out various tests to evaluate the quality of generated DSMs regarding robustness and precision. The results have verified that the presented pipeline of DSM generation from high resolution satellite imagery is applicable, reliable and very promising. [ABSTRACT FROM AUTHOR]

As the need for efficient methods to accurately update and refine geospatial satellite image databases is increasing, we have proposed the use of 3-dimensional digital maps for the fully-automated RPCs bias compensation of high resolution satellite imagery. The basic idea is that the map features are scaled and aligned to the image features, except for the local shift, through the RPCs-based image projection, and then the shifts are automatically determined over the entire image space by template-based edge matching of the heterogeneous data set. This enables modeling of RPCs bias compensation parameters for accurate georeferencing. The map features are selected based on four suggested rules. Experiments were carried out for three Kompsat-2 images and stereo IKONOS images with 1:5000 scale Korean national topographic maps. Image matching performance is discussed with justification of the parameter selection, and the georeferencing accuracy is analyzed. The experimental results showed the automated approach can achieve one-pixel level of georeferencing accuracy, enabling economical hybrid map creation as well as large scale map updates. [ABSTRACT FROM AUTHOR]

Abstract: Resistive Plate Chambers (RPCs) are widely used in high energy physics. While avalanche mode operation is mandatory in high rate environments (ATLAS and CMS experiments at LHC), streamer mode operation is often preferred in low rate applications because of the high signal amplitude. Typical mixtures for streamer operation are composed of Argon, Tetrafluoroethane and Isobutane, with additions of SF6 below 1% to reduce the charge delivered in the gas. In this paper, results about the streamer properties observed with different mixtures are presented. [Copyright &y& Elsevier]

Abstract: Detailed performance simulations of the HADES RPC time-of-flight wall have been undertaken. The most delicate situation is the identification of mesons close to the mid-rapidity region. While momentum resolution does not appear to be an issue, the small non-Gaussian tails in the time response are a clear problem. It will be argued that the use of redundant information supplied by time coincidence between the two layers (possible in the HADES design) can drastically improve the situation. The uniformity of acceptance for the two layer coincidence will be discussed. A possible distortion to the reconstructed kaon flow due to the wall occupancy, which is not isotropic with respect to the reaction plane because of the flow pattern of the much more abundant protons, pions and deuterons, has also been studied. [Copyright &y& Elsevier]

Abstract: The measurement of YBJ-ARGO Resistive Plate Chamber (RPC), working in avalanche mode was performed. With different component of i-C4H10 in C2H2F4-based gas mixtures C2H2F4/i-C4H10/SF6, the behavior of the detector with respect to the high voltage was studied. The experiment confirms that it is possible to operate YBJ-ARGO RPC in avalanche mode. The results show that with the gas mixtures containing 10% of i-C4H10 the detector achieves its optimum performance. [Copyright &y& Elsevier]

The RPC detectors in the L3 experiment at LEP work as a trigger system for the Forward–Backward Muon Spectrometer. It consists of 192 bi-gap RPCs working in streamer mode. We monitored the behaviour of the system over seven years of data taking at LEP. To investigate the ageing of the RPCs after this long-term operation, we report the main results obtained from 1994 to 2000, together with the results of tests performed on some RPC chambers in our test site in Napoli with cosmic rays after the dismantling of L3. [Copyright &y& Elsevier]

The BaBar experiment uses a big system based on RPC detectors to discriminate muons from pions and to identify neutral hadrons. About 2000 m2 of RPC chambers have been working at SLAC since the end of 1998. We report on the performances of the RPC chambers focusing on new problems discovered in the RPC behaviour. These problems started very soon after the installation of the chambers on the detector when the high-ambient temperature triggered an increase of dark currents inside the chambers and a reduction of the efficiency. Careful analysis of the BaBar data and dedicated R&D efforts in the laboratory have helped to identify the main source of the trouble in the linseed oil varnish on the bakelite electrodes. [Copyright &y& Elsevier]

Bakelite RPCs, assembled according to the ARGO design, have been operated in the high altitude Laboratory of YBJ using dedicated electronics to pick-up the streamer signal. Here we report on the results concerning absorbed current, single counting rate, efficiency and time resolution. Environmental data concerning the operating temperature inside the ARGO experimental hall are also reported. [Copyright &y& Elsevier]

The fluctuation theory for the avalanche growth with and without space charge effects is briefly summarized and compared to a broad field of applications. These include spark counters as well as timing and trigger RPCs operated in avalanche mode. A large domain in electrical field strength, pressure, gap size and gas mixture type is covered. A reasonable agreement with the experiment is observed, giving confidence on the validity of both assumptions and treatment of the theory. [Copyright &y& Elsevier]

In the present paper we describe a search for gases that allow to reduce the energy of the electrical discharge produced in Resistive Plate Chambers (RPCs) operated in streamer mode, by reducing both the operating voltage and the released charge. This can be achieved, with current gas mixtures of argon, tetrafluoroethane (TFE) and isobutane, by reducing the total amount of quenching components (TFE+isobutane) down to 10–15% and compensating for the lower gas quenching power with the addition of small amounts of SF6. We show here that SF6, even for concentrations as low as 1% or less, has a strong effect in reducing the delivered charge in low quenched gases and allows to achieve a proper working mode of the RPC even at voltages as low as 4–5 kV over a 2 mm gas gap. [Copyright &y& Elsevier]

We discuss the signal propagation, strip termination and crosstalk in resistive plate chambers (RPCs) by analyzing the explicit time domain solution of a two dimensional multi-conductor transmission line. It is shown that all the effects can be calculated by elementary matrix manipulations. It is also shown that losses should not play a role for frequencies <200 MHz. [Copyright &y& Elsevier]

Epipolar images can improve the efficiency and accuracy of dense matching by restricting the search range of correspondences from 2-D to 1-D, which play an important role in 3-D reconstruction. As most of the satellite images in archives are incidental collections, which do not have rigorous stereo properties, in this paper, we propose a general framework to generate epipolar images for both in-track and cross-track stereo images. We first investigate the theoretical epipolar constraints of single-sensor and multi-sensor images and then introduce the proposed framework in detail. Considering large elevation changes in mountain areas, the publicly available digital elevation model (DEM) is applied to reduce the initial offsets of two stereo images. The left image is projected into the image coordinate system of the right image using the rational polynomial coefficients (RPCs). By dividing the raw images into several blocks, the epipolar images of each block are parallel generated through a robust feature matching method and fundamental matrix estimation, in which way, the horizontal disparity can be drastically reduced while maintaining negligible vertical disparity for epipolar blocks. Then, stereo matching using the epipolar blocks can be easily implemented and the forward intersection method is used to generate the digital surface model (DSM). Experimental results on several in-track and cross-track images, including optical-optical, SAR-SAR, and SAR-optical pairs, demonstrate the effectiveness of the proposed framework, which not only has obvious advantages in mountain areas with large elevation changes but also can generate high-quality epipolar images for flat areas. The generated epipolar images of a ZiYuan-3 pair in Songshan are further utilized to produce a high-precision DSM. [ABSTRACT FROM AUTHOR]

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Kompsat-3/3A provides along-track and across-track stereo data for accurate three-dimensional (3D) topographic mapping. Stereo data preprocessing involves conjugate point extraction and acquisition of ground control points (GCPs), rational polynomial coefficient (RPC) bias compensation, and epipolar image resampling. Applications where absolute positional accuracy is not a top priority do not require GCPs, but require precise conjugate points from stereo images for subsequent RPC bias compensation, i.e., relative orientation. Conjugate points are extracted between the original stereo data using image-matching methods by a proper outlier removal process. Inaccurate matching results and potential outliers produce geometric inconsistency in the stereo data. Hence, the reliability of conjugate point extraction must be improved. For this purpose, we proposed to apply the coarse epipolar resampling using raw RPCs before the conjugate point matching. We expect epipolar images with even inaccurate RPCs to show better stereo similarity than the original images, providing better conjugate point extraction. To this end, we carried out the quantitative analysis of the conjugate point extraction performance by comparing the proposed approach using the coarsely epipolar resampled images to the traditional approach using the original stereo images. We tested along-track Kompsat-3 stereo and across-track Kompsat-3A stereo data with four well-known image-matching methods: phase correlation (PC), mutual information (MI), speeded up robust features (SURF), and Harris detector combined with fast retina keypoint (FREAK) descriptor (i.e., Harris). These matching methods were applied to the original stereo images and coarsely resampled epipolar images, and the conjugate point extraction performance was investigated. Experimental results showed that the coarse epipolar image approach was very helpful for accurate conjugate point extraction, realizing highly accurate RPC refinement and sub-pixel y-parallax through fine epipolar image resampling, which was not achievable through the traditional approach. MI and PC provided the most stable results for both along-track and across-track test data with larger patch sizes of more than 400 pixels. [ABSTRACT FROM AUTHOR]

The trigger for the Barrel Muon Spectrometer of the ATLAS experiment at LHC will be given by means of Resistive Plate Chambers working in avalanche mode. Before being mounted on the experimental apparatus each RPC chamber will undergo detailed quality control tests. A dedicated cosmic rays test station with good tracking resolution is operational in Naples University and INFN laboratory. All working parameters of RPCs are monitored and measured. Moreover, the uniformity of the efficiency on the whole surface is measured. A brief description of the test station and results for the first 148 Units will be presented. [Copyright &y& Elsevier]

Abstract: An easy and fast matrix formalism for the tracking of charged particles through timing detectors is presented. The method is based on the least squares method and works directly with the first level data, that is, positions and readout times provided by timing detectors. In one step it provides the coordinates, the slopes, the velocity and an offset time at a given reference plane. The formalism is applied to some examples. [Copyright &y& Elsevier]