Final Data Quality Research Articles

Monitoring functional immune responses with a cytokine release assay: ISS flight hardware design and experimental protocol for whole blood cultures executed under microgravity conditions.

Introduction: Long-term space missions trigger a prolonged neuroendocrine stress response leading to immune system dysregulation evidenced by susceptibility to infections, viral reactivation, and skin irritations. However, due to existing technical constraints, real-time functional immune assessments are not currently available to crew inflight. The in vitro cytokine release assay (CRA) has been effectively employed to study the stimulated cytokine response of immune cells in whole blood albeit limited to pre- and post-flight sessions. A novel two-valve reaction tube (RT) has been developed to enable the execution of the CRA on the International Space Station (ISS). Methods: In a comprehensive test campaign, we assessed the suitability of three materials (silicone, C-Flex, and PVC) for the RT design in terms of biochemical compatibility, chemical stability, and final data quality analysis. Furthermore, we thoroughly examined additional quality criteria such as safety, handling, and the frozen storage of antigens within the RTs. The validation of the proposed crew procedure was conducted during a parabolic flight campaign. Results: The selected material and procedure proved to be both feasible and secure yielding consistent and dependable data outcomes. This new hardware allows for the stimulation of blood samples on board the ISS, with subsequent analysis still conducted on the ground. Discussion: The resultant data promises to offer a more accurate understanding of the stress-induced neuroendocrine modulation of immunity during space travel providing valuable insights for the scientific community. Furthermore, the versatile nature of the RT suggests its potential utility as a testing platform for various other assays or sample types.

Flight Path Setting and Data Quality Assessments for Unmanned-Aerial-Vehicle-Based Photogrammetric Bridge Deck Documentation.

Imagery from Unmanned Aerial Vehicles can be used to generate three-dimensional (3D) point cloud models. However, final data quality is impacted by the flight altitude, camera angle, overlap rate, and data processing strategies. Typically, both overview images and redundant close-range images are collected, which significantly increases the data collection and processing time. To investigate the relationship between input resources and output quality, a suite of seven metrics is proposed including total points, average point density, uniformity, yield rate, coverage, geometry accuracy, and time efficiency. When applied in the field to a full-scale structure, the UAV altitude and camera angle most strongly affected data density and uniformity. A 66% overlapping was needed for successful 3D reconstruction. Conducting multiple flight paths improved local geometric accuracy better than increasing the overlapping rate. The highest coverage was achieved at 77% due to the formation of semi-irregular gridded gaps between point groups as an artefact of the Structure from Motion process. No single set of flight parameters was optimal for every data collection goal. Hence, understanding flight path parameter impacts is crucial to optimal UAV data collection.

СТАТИСТИЧНЕ ПЛАНУВАННЯ КЛІНІЧНИХ ДОСЛІДЖЕНЬ, ПОДАЛЬШИЙ РИЗИК-МЕНЕДЖМЕНТ, ВЗАЄМОДІЯ СПОНСОРА І КДО

Statistical planning of clinical trials (CT) is the starting point for the project, since its results determine the sample of patients, the size of which completely depends on the design of the future study, the number of involved countries, clinical sites, as well as the strategy of further management - the budget, human resources, vendors, etc. The purpose of the article is to analyze the influence of the selection of the sample size of patients, as well as the main risks, the management of risks that may arise during the KD due to incorrect calculation of the sample, the interaction of the sponsor and the KDO in the management of such risks. The sponsor in the CT is the organization that carries out the development of the drug, as well as invests in the CT, while the contract research organization (CRO) performs part of the project work, functions and responsibilities, that are being delegated by the sponsor. The degree of integration of CRO into CT as a project is important, at the same time, concentration exclusively on the tasks set by the Sponsor may have a negative impact on the quality and volume of final statistical data of the CT, as the presence of insufficient data volume to prove the hypothesis, in fact, is the main risk of "failure" of the project. The key is a correct understanding of the basic initial tasks by the CRO, the logic of constructing the hypothesis proof, the adoption of its main components, even if the CRO is not involved in the process of statistical planning itself. The CRO may not be directly involved in this process - it is important that the Sponsor makes sure before the start of the CT that the vendor in the person of the CRO has accepted the basic concept of the CT. Such interaction and mutual understanding will help to effectively and efficiently build optimal management, control the progress of the project, and resist possible risks in the future.

Does Sport Participation Protect Adolescents from Alcohol Consumption? A Scoping Review.

(1) Background: Participation in youth sports is believed to protect against alcohol consumption. Although this concept has been questioned for over 40 years, the review of methodologically reliable evidence data is scarce. This review summarizes the state of knowledge on the association between practicing sports and alcohol consumption among adolescents (10-19 years old) and its moderators. (2) Methods: The review covers only random-sample-based and population research. A systematic search was conducted on Scopus, PubMed, and WoS, for articles published between 2000 and 2021. From the 1944 identified records, 139 advanced to the full-text review, and 32 to the final data extraction and quality review. (3) Results: About two-thirds of the studies, including all the longitudinal ones, showed a positive association between sport participation and alcohol consumption. The most common mediators were gender (males were at higher risk), discipline (odds for team sports were higher, but professionalization could reduce it), and race, which intersected with gender, putting white males at the highest risk. (4) Conclusions: Further longitudinal research based on random samples using standardized indicators, including psychological and social variables, may provide more consistent outcomes and allow for the identification of mediating mechanisms.

Challenges, limitations, and measurement strategies to ensure data quality in deep-sea sensors

In this paper we give an overview of factors and limitations impairing deep-sea sensor data, and we show how automatic tests can give sensors self-validation and self-diagnostic capabilities. This work is intended to lay a basis for sophisticated use of smart sensors in long-term autonomous operation in remote deep-sea locations. Deep-sea observation relies on data from sensors operating in remote, harsh environments which may affect sensor output if uncorrected. In addition to the environmental impact, sensors are subject to limitations regarding power, communication, and limitations on recalibration. To obtain long-term measurements of larger deep-sea areas, fixed platform sensors on the ocean floor may be deployed for several years. As for any observation systems, data collected by deep-sea observation equipment are of limited use if the quality or accuracy (closeness of agreement between the measurement and the true value) is not known. If data from a faulty sensor are used directly, this may result in an erroneous understanding of deep water conditions, or important changes or conditions may not be detected. Faulty sensor data may significantly weaken the overall quality of the combined data from several sensors or any derived model. This is particularly an issue for wireless sensor networks covering large areas, where the overall measurement performance of the network is highly dependent on the data quality from individual sensors. Existing quality control manuals and initiatives for best practice typically recommend a selection of (near) real-time automated checks. These are mostly limited to basic and straight forward verification of metadata and data format, and data value or transition checks against pre-defined thresholds. Delayed-mode inspection is often recommended before a final data quality stamp is assigned.

Sequence Capture From Historical Museum Specimens: Maximizing Value for Population and Phylogenomic Studies

The application of high-throughput, short-read sequencing to degraded DNA has greatly increased the feasibility of generating genomic data from historical museum specimens. While many published studies report successful sequencing results from historical specimens; in reality, success and quality of sequence data can be highly variable. To examine predictors of sequencing quality, and methodological approaches to improving data accuracy, we generated and analyzed genomic sequence data from 115 historically collected museum specimens up to 180 years old. Data span both population genomic and phylogenomic scales, including historically collected specimens from 34 specimens of four species of Australian rock-wallabies (genus Petrogale) and 92 samples from 79 specimens of Australo-Papuan murine rodents (subfamily Murinae). For historical rodent specimens, where the focus was sampling for phylogenomics, we found that regardless of specimen age, DNA sequence libraries prepared from toe pad or bone subsamples performed significantly better than those taken from the skin (in terms of proportion of reads on target, number of loci captured, and data accuracy). In total, 93% of DNA libraries from toe pad or bone subsamples resulted in reliable data for phylogenetic inference, compared to 63% of skin subsamples. For skin subsamples, proportion of reads on target weakly correlated with collection year. Then using population genomic data from rock-wallaby skins as a test case, we found substantial improvement in final data quality by mapping to a high-quality “closest sister” de novo assembly from fresh tissues, compared to mapping to a sample-specific historical de novo assembly. Choice of mapping approach also affected final estimates of the number of segregating sites and Watterson's θ, both important parameters for population genomic inference. The incorporation of accurate and reliable sequence data from historical specimens has important outcomes for evolutionary studies at both population and phylogenomic scales. By assessing the outcomes of different approaches to specimen subsampling, library preparation and bioinformatic processing, our results provide a framework for increasing sequencing success for irreplaceable historical specimens.

Selecting a pre-processing pipeline for the analysis of EEG event-related rhythms modulation.

When deciding how to pre-process EEG data, researchers need to make a choice at each single step of the procedure among different possibilities, equally valid. Therefore, in this work, we illustrate how these decisions may affect the quality of the final cleaned data in an Action Observation/Motor Imagery protocol, using quantitative indices. In particular, we showed the effect of segmenting or not the data in epochs around the stimulus presentation time on the independent component analysis (ICA) used for artifact removal. For ICA analysis, we tested two algorithms (SOBI and Extended Infomax). Finally, three re-reference approaches (Common averaged reference-CAR, robust-CAR and reference electrode standardization technique - REST) were also applied and their effects compared. Results showed that the segmenting method has a prominent effect on the cleaning procedure and consequently on final EEG data quality. Extended Infomax is confirmed as the method of choice for the identification of the artifactual components and, finally, CAR and the REST re-referencing techniques led to similar good results.

The Undesirable Effects and Impacts of Ice Contamination Experienced in the Cryo-Electron Tomography Workflow and Available Solutions

Abstract:Cryo-electron tomography (cryo-ET) is a powerful technique that can provide unprecedented insight into protein-protein interactions and molecular machinery in a near-native state. The adoption of cryo-ET by life science research groups is hampered by the challenges associated with cryo-ET sample preparation. The current sample preparation process has many steps at which ice contamination may occur to negatively affect the final sample and data quality. A survey was conducted to better understand the effects and impact of ice contamination to the cryo-ET outcome. Over 80 cryo-electron microscopy users worldwide participated in our survey. The results are presented in this article. We furthermore discussed the currently available solutions that can alleviate the ice contamination problems to increase the sample yield and cryo-ET data output.

Abstract P-4: Robust Method for Background Subtraction in Serial X-ray Diffraction Data

Background: Membrane receptors play an important role in signal transduction across the cell membrane in all living organisms. Their structural studies have been enabled by multiple technological breakthroughs in their heterologous expression, stabilization, crystallization, and crystallographic data collection as well as in cryogenic electron microscopy (cryoEM). During the last decade, serial femtosecond crystallography (SFX) using X-ray free electron lasers (XFELs) has enabled structure determination of previously inaccessible proteins, including several G-protein-coupled receptors (GPCR), that produce only micrometer-sized crystals, thus paving the way towards understanding their activation mechanism and rational drug discovery. In addition to experimental difficulties, membrane protein structure determination is also often accompanied by data processing challenges. In particular, the lipidic cubic phase that serves as a carrier for membrane protein microcrystals, as well as various XFEL beam-shaping devices may generate substantial background scattering that could complicate the structure factor extraction from the diffraction images. Methods: In this work, we tested an adaptation of the denoising algorithm via matrix decomposition to XFEL-SFX data. We benchmarked its performance using high-background data from PAL-XFEL and established its applicability to serial crystallography image denoising, as well as compared it to the CrystFEL-based image denoising algorithm. Results: We find that, although the decomposition-based image denoising does not outperform CrystFEL median subtraction, it performs better than the integration without any additional subtraction. We find the non-negative matrix factorization performing better than more traditional singular-value decomposition methods, both in terms of visual interpretability and final data quality. Conclusion: We hope that this work will draw attention to background subtraction methods in structural biology, and will pave the way towards processing of most challenging datasets in structural biology, in particularly, those collected from membrane proteins.

Results from a Phase 1 Dose Escalation Study of HMPL-689, a Selective Oral Phosphoinositide 3-Kinase-Delta Inhibitor, in Chinese Patients with Relapsed/Refractory (R/R) Lymphomas

Introduction HMPL-689 is a potent and highly selective small molecule inhibitor of phosphoinositide 3-kinase-delta (PI3Kδ). Despite available agents targeting the B-cell receptor (BCR) pathway, there remains a need for alternative therapies in the relapsed/refractory (R/R) setting due to agent-specific toxicities and suboptimal efficacy among lymphoma subtypes. This study (NCT03128164) is a phase 1, open-label, dose escalation and expansion study in China to assess the safety, pharmacokinetics (PK), and preliminary efficacy of HMPL-689 as a monotherapy in patients with R/R lymphomas. Here we present the preliminary results of the dose-escalation phase of the study. Methods In this dose escalation phase, patients with R/R lymphoma failed of standard therapy, at least 1 prior therapy, were eligible. The dose-escalation study consisted of cohort A (BID) and cohort B (QD), in which HMPL-689 was orally administered continuously on a 28-day cycle. The modified toxicity probability interval scheme-2 (mTPI-2) design was applied for the dose escalation and maximum tolerated dose (MTD) determination. Blood samples for PK and pharmacodynamics (PD) analyses were collected during Cycle 1 and Day 1 of each subsequent cycle. Results A total of 56 patients were enrolled, with 5 chronic lymphocytic leukemia/small lymphocytic lymphoma (CLL/SLL), 23 follicular lymphoma (FL), 7 marginal zone lymphoma (MZL), 9 mantle cell lymphoma (MCL), 9 diffuse large B cell lymphoma (DLBCL), and 3 Hodgkin's lymphoma (HL) patients (Table 1). The median age was 56 years (range 26-73). The median number of prior therapies was 3 (range 1-8), of which 39 patients had prior exposure to rituximab. 29 patients received HMPL-689 in cohort A (BID): 2.5 mg (n=3), 5 mg (n=9), 7.5 mg (n=8), and 10 mg (n=9), while 27 patients were in cohort B (QD): 5 mg (n=3), 10 mg (n=3), 20 mg (n=9), 30 mg (n=9), and 40 mg (n=3). Median duration of HMPL-689 therapy was 7.6 months (range 0.4 -Not reached [NR]). The most common Grade ≥3 non-hematologic treatment emergent adverse events (TEAEs) were pneumonia and hypertension. Grade ≥3 hematologic TEAEs were neutropenia (Table 2). No Grade 5 TEAE was reported. In cohort A, 4 dose limited toxicities (DLTs) were observed, including Grade 3 asymptomatic amylase (2 pts, 5 mg), Grade 4 hypercalcemia (1 pt, 10 mg), Grade 3 lipase increased (1 pt, 10 mg). In cohort B, 5 DLTs including Grade 3 skin maculopapular (1 pt, 20 mg), hypertriglyceridemia (1 pt, 30 mg), QT interval prolongation (1 pt, 30 mg) and rash (2 pts, 40 mg) were reported. Plasma PK data for the 5-30 mg QD and 2.5-10 mg BID multiple-dose regimens were determined. HMPL-689 drug exposures increased in a dose proportional fashion up to 30mg QD, as reflected in AUC and Cmax. The geometric mean AUCtau and Cmax at 30 mg QD in patients were approximately 2150 h•ng/mL and 260 ng/mL, respectively at steady state. The median Tmax was around 2 h and the arithmetic mean t1/2 was within the range of 5-10 hours, consistent across all dose levels. 51 out of the 56 patients had post-baseline tumor assessment, with 6 complete response (CR) (2 CLL/SLL, 4 FL), 21 partial responses (PR) (2 CLL/SLL, 5 MZL, 7 FL, 4 MCL, 3 DLBCL) and 18 stable disease (SD) (2 MZL, 9 FL, 4 MCL, 1 DLBCL, 2 HL). This resulted in 52.9% (27/51) objective response rate (ORR) in efficacy evaluable patients. The median time to response (TTR) and duration of response (DOR) were 3.5 months (1.8-8.4) and 6.4 months (0.7-NR), respectively (Table 3). One patient with FL who achieved CR (per post hoc independent radiologic review) was on treatment > 586 days. Final data quality control/verification is ongoing. As a result, 30 mg QD of HMPL-689 has been selected as recommended phase 2 dose (RP2D) based on overall safety and tolerability, PK/PD and preliminary efficacy data. Conclusions: HMPL-689 was well tolerated and the RP2D was determined to be 30 mg QD orally. It exhibited dose-proportional pharmacokinetics, a manageable toxicity profile, and promising single-agent clinical activity in R/R B-cell lymphoma patients. The dose expansion study is ongoing, evaluating the safety and efficacy of HMPL-689 in patients with R/R B-cell lymphoma. Acknowledgement 1. We would like to thank all patients and their families who participated in this trial; 2. We would like to thank all investigators, study coordinators and the entire project team. Disclosures Duan: Hutchison MediPharma Limitied: Current Employment. Yu:Hutchison MediPharma Limitied: Current Employment. Cai:Hutchison MediPharma Limitied: Current Employment. Su:Hutchison MediPharma Limited: Current Employment.

High-Quality UAV-Based Orthophotos for Cadastral Mapping: Guidance for Optimal Flight Configurations

During the past years, unmanned aerial vehicles (UAVs) gained importance as a tool to quickly collect high-resolution imagery as base data for cadastral mapping. However, the fact that UAV-derived geospatial information supports decision-making processes involving people’s land rights ultimately raises questions about data quality and accuracy. In this vein, this paper investigates different flight configurations to give guidance for efficient and reliable UAV data acquisition. Imagery from six study areas across Europe and Africa provide the basis for an integrated quality assessment including three main aspects: (1) the impact of land cover on the number of tie-points as an indication on how well bundle block adjustment can be performed, (2) the impact of the number of ground control points (GCPs) on the final geometric accuracy, and (3) the impact of different flight plans on the extractability of cadastral features. The results suggest that scene context, flight configuration, and GCP setup significantly impact the final data quality and subsequent automatic delineation of visual cadastral boundaries. Moreover, even though the root mean square error of checkpoint residuals as a commonly accepted error measure is within a range of few centimeters in all datasets, this study reveals large discrepancies of the accuracy and the completeness of automatically detected cadastral features for orthophotos generated from different flight plans. With its unique combination of methods and integration of various study sites, the results and recommendations presented in this paper can help land professionals and bottom-up initiatives alike to optimize existing and future UAV data collection workflows.

Application of Ground-Penetrating Radar Broadband Antenna in Underground Detection

When GPR is detecting unknown objects underground, different antenna working frequency, different antenna size and different antenna internal structure will affect the final data quality and ultimately affect the detection accuracy of GPR. Therefore, when actualizing and evaluating the uwb signal of GPR electromagnetic wave, the electromagnetic properties of underground medium should be fully considered, and the influence of relevant parameters of GPR antenna on the transmitted and received electromagnetic signals should be analyzed by using numerical analysis method. This paper mainly describes the design characteristics of GPR antenna and antenna array, as well as the types, characteristics and application convenience of antenna array under different positioning purposes of GPR.

EVALUATION OF AN INTEGRATIVE APPROACH BETWEEN HBIM AND ARCHITECTURE HISTORY

Abstract. Restorative and conservative operations of Cultural Heritage buildings involve the historical and objective knowledge of the context. Meaning the knowledge as a diachronic awareness of the history of buildings should help the safeguarding processes of heritage assets.The integration of historical information inside a HBIM platform involves huge benefits for the Cultural Heritage case management, its periodical monitoring operations and valorisation processes, moreover the historical evolution is correctly considered. This solution allows to maximize the comprehension and also communication of the analysed context through few simple steps as visualize, read and query in order to ensure the accuracy and quality of final data (Diara et al, 2018).This new court of methodologic cooperation will be tested on the case study of the medieval Abbey of Staffarda (CN, Italy) and its refectory in a deeper way where, thanks to recent studies, it has been possible to reconstruct analysis map for a complete vision of the church and the Abbey’s complex as well (Beltramo et al, 2019).

The Data Quality Monitoring Software for the CMS experiment at the LHC: past, present and future

The Data Quality Monitoring software is a central tool in the CMS experiment. It is used in the following key environments: (i) Online, for real-time detector monitoring; (ii) Offline, for the prompt-offline-feedback and final fine-grained data quality analysis and certification; (iii) Validation of all the reconstruction software production releases; (iv) Validation in Monte Carlo productions. Though the basic structure of the Run1 DQM system remains the same for Run2, between the Run1 and Run2 periods, the DQM system underwent substantial upgrades in many areas, not only to adapt to the surrounding infrastructure changes, but also to provide improvements to meet the growing needs of the collaboration with an emphasis on more sophisticated methods for evaluating data quality. We need to cope with the higher-energy and -luminosity proton-proton collision data, as well as the data from various special runs, such as Heavy Ion runs. In this contribution, we will describe the current DQM software, structure and workflow in the different environments. We then discuss the performance and our experiences with the DQM system in Run2. The main technical challenges which we have encountered and the solutions adopted during Run2 will also be discussed, including efficient use of memory in multithreading environments. Finally, we present the prospect of a future DQM upgrade with emphasis on functionality and long-term robustness for LHC Run3.

Performance Evaluation of TanDEM-X Quad-Polarization Products in Bistatic Mode

In the TanDEM-X mission, quad-polarization data (HH, HV, VH, and VV-polarization channels) can be acquired at an experimental basis by acquiring images in the dual-receive antenna (DRA) mode. This mode was activated during the so-called TanDEM-X science phase, from October 2014 up to January 2016, serving the science community with a unique dataset for the demonstration of new SAR techniques and applications. Quad-polarization data has been firstly acquired in pursuit monostatic mode and, secondly, in bistatic configuration as well. TanDEM-X is the first spaceborne mission which allows for the acquisition of quad-polarization data in bistatic formation, with across-track baselines varying up to 4 km at the Equator. The current work completes the one presented in [1] , where TanDEM-X quadpolarization data, acquired in pursuit monostatic mode only, was analyzed and recommendations were drawn, in order to optimize the acquisition parameters, aiming at improving the final data quality. Such recommendations were then taken into account for the acquisition of quad-polarization data in bistatic configuration, starting from April 2015, and the obtained results are presented in this paper. Investigations have been performed, aiming at monitoring the effective improvement in data quality. For example, we investigated the impact of different system parameters, such as noise equivalent sigma zero (NESZ) or processing bandwidth on the SAR performance, together with their influence on the interferometric SAR (InSAR) performance, assessed in terms of interferometric coherence and relative height error. Finally, we introduce and discuss an experimental acquisition mode, which allows to synthesize a quad-polarization product by combining two simultaneous dual-polarization acquisitions.

A Method for Developing Data Quality Measures and Metrics for Primary Health Care

The secondary use of primary care data has many potential applications. By using data from a local primary care organization, a method for developing data quality measures and metrics in primary care is presented as a case study. The method that was created included an exploratory meeting with a subject matter expert, the creation of a first draft of measures with the information management team, the discussion of the proposed measures with a focus group and a final data quality report encompassing all the collected feedback. The method was used to create rules and formulae to measures timeliness, completeness, accuracy and usefulness in the primary care ecosystem. Future work will involve completing a detailed quantitative analysis of the data quality measures calculated with the proposed metrics. In the future these measures can be broken down and compared on a monthly, professional and users basis to provide insight into the behavior and nuance of data quality in primary care.

Combining survey and administrative data in Italian business surveys

The main Italian enterprise surveys are shifting from a simple traditional data collection approach to a more complex one. This new approach is based on survey database management involving the recasting of many data sources (including administrative data). The reasons for utilising administrative data are: improved timeliness, increased precision and a reduction in the statistical burden. In our paper we focus on the Italian SCI survey (Sistema dei Conti delle Imprese, i.e., Businesses accounts survey). A number of innovations have been introduced into this survey over the last few years and remain ongoing. Since 2005, final economic estimates are obtained combining various data sources, primarily administrative data. The integration procedure involves a number of methodological solutions. In this paper we deal with the problem of non-response, particularly unit non-response. At first methodological issues, research and applicative trends in the NSI (National Statistical Institute) are briefly reviewed. Afterwards alternative means of estimating business data using administrative records and integrating sources are applied to the SCI survey data. The integration procedure is presented and its impact on the improvement of final data quality is verified.

The Attribute Accuracy Assessment of Land Cover Data in the National Geographic Conditions Survey

Abstract. With the widespread national survey of geographic conditions, object-based data has already became the most common data organization pattern in the area of land cover research. Assessing the accuracy of object-based land cover data is related to lots of processes of data production, such like the efficiency of inside production and the quality of final land cover data. Therefore，there are a great deal of requirements of accuracy assessment of object-based classification map. Traditional approaches for accuracy assessment in surveying and mapping are not aimed at land cover data. It is necessary to employ the accuracy assessment in imagery classification. However traditional pixel-based accuracy assessing methods are inadequate for the requirements. The measures we improved are based on error matrix and using objects as sample units, because the pixel sample units are not suitable for assessing the accuracy of object-based classification result. Compared to pixel samples, we realize that the uniformity of object samples has changed. In order to make the indexes generating from error matrix reliable, we using the areas of object samples as the weight to establish the error matrix of object-based image classification map. We compare the result of two error matrixes setting up by the number of object samples and the sum of area of object samples. The error matrix using the sum of area of object sample is proved to be an intuitive, useful technique for reflecting the actual accuracy of object-based imagery classification result.

The filtering and compressing of outer beams to multibeam bathymetric data

Some errors and noises are often present in multibeam swath bathymetric data. Echo detection error (EDE) is one of the main errors. It causes the depth error to become bigger in outer beams and looks like sound refraction. But depth errors due to EDEs have a trumpet-shaped appearance, instead of a curved appearance that is caused by the sound refraction errors. EDEs, including systematic acoustic signal detection errors and internal noises, cannot be removed during the correction of sound refraction. It causes depth inconsistencies between adjacent swaths and degrades precision of outer beams. Sometimes, the bathymetric errors caused by EDEs do not even meet the requirements of IHO (International Hydrographic Organization). Therefore, a post-processing method is presented to minimize the EDEs by filtering outliers and compressing outer beams of multibeam bathymetric data. The outliers caused by internal noises are removed by an automatic filter algorithm first. Then the outer beams are compressed to reduce systematic acoustic signal detection errors according to their depths, the calculated depth line and standard deviations (SDs). The automatic filter process is important for calculating the depth line. The selection of inner beams to calculate the average SD of beam depths is crucial to achieving compressing goals. The quality of final bathymetric data in outer beams can be improved by these steps. The method is verified by a field test.

ATLAS tile calorimeter data quality assessment and performance with calibration, cosmic and first beam data

The commissioning of the barrel hadronic calorimeter (Tile) of the ATLAS detector at the Large Hadron Collider (LHC) has been the focus of an extensive project over the last several years. Work with Tile has resulted in a fully operational detector before the first LHC beam test on 10 September 2008. A set of tools has been developed spanning from the hardware and software systems of the detector and online monitoring to the offline reconstruction. This set of tools constitutes the final Tile data quality system and is highly integrated with all ATLAS online and offline frameworks. A review of the final data quality system of the Tile hadronic calorimeter will be presented together with selected results on hardware reliability. This will be followed by the detector performance checks performed on cosmic data and on the first LHC beam data taken on 10 September 2008.