Reduce Sampling Error Research Articles

Adaptive sampling point planning for free-form surface inspection under multi-geometric constraints

Free-form surfaces have been widely used in aerospace, automotive and other fields. Due to its complex geometry, free-form surface inspection is generally conducted by touch-trigger or measuring probe-based Coordinate Measurement Machines or On-machine Measurement. Sampling strategy plays a decisive role in improving both measurement accuracy and efficiency, which is determined by sample size and distribution of sample points. However, it is difficult to simultaneously take the surface curvature, sampling density and approximation error into account, considering the complexity of surface geometry. In this paper, triangle mesh simplification is innovatively adopted in sampling planning to achieve multi-geometric constraints. As triangle mesh has outstanding advantages in representing the surface features, strong stability and is easy to modify its structure, free-form surface is converted to a dense triangle mesh. Triangle mesh simplification is implemented by iteratively contracting triangle edges. An improved quadric error metric is established to decide contraction order and optimal target vertices under discrete curvature constraint. Sampling density is controlled by limiting the triangle edge length. Detailed adaptive sampling algorithm under multi-geometric constraints is then developed. Both simulation and experiment are conducted to validate feasibility and robustness of the proposed method. The results are compared with uniform sampling and existing adaptive sampling strategy to show that the proposed method can prominently reduce sampling error when sample size is small.

A Computationally Efficient Ensemble Filtering Scheme for Quantitative Volcanic Ash Forecasts

AbstractA method of assimilating satellite observations in quantitative ensemble forecasting models of airborne volcanic ash is presented in this study. The method employs many trial dispersion model simulations that are generated by both deterministic and random perturbations of the source term and use of an ensemble of numerical weather prediction model fields. An ensemble filter is then applied to the trial simulations, which are either selected or rejected by the filter based on their degree of agreement with observations within a specified time window. The observations may be in the form of quantitative satellite retrieved mass load fields or qualitative ash detection fields, which means that useful results can be obtained even when retrievals are not available in real time provided that the ash boundaries can be identified. The filtering process is repeated several times with different random realizations of the source term to reduce sampling error and minimize filter degeneracy, a phenomenon that plagues all ensemble filter models. The selected members are then propagated forward in time beyond the observational time window to form the forecast ensemble. We show, using several eruption case studies, that forecast ensembles constructed in this way are generally superior in skill to reference forecasts that do not assimilate observations.

Pathological features and pathological diagnosis of drug-induced liver injury

Based on liver histology, drug-induced liver injury (DILI) is classified as various pathological types of inflammatory necrosis, cholestasis, fatty degeneration and fatty liver disease, vascular injury, and minimal lesion. Histopathological examination is required for further differential diagnosis in suspected cases of DILI, liver injury that cannot be explained by DILI monogenesis, DILI cases with a history of exposure to various drugs in which the specific drug causing liver injury cannot be determined, DILI cases with unsatisfactory treatment outcome, and chronic DILI, and histopathological examination can also be used to evaluate the severity and prognosis of DILI. Since liver lesions are unevenly distributed in DILI, adequate tissue samples are needed to reduce sampling error. The histopathological manifestation of liver injury diseases has the features of cause with multiple results and one result with multiple causes, and a combination of pathological examination and clinical symptoms can help to make a confirmed diagnosis, suggesting that clinicopathological discussion is of great importance in the histological diagnosis of DILI.

Standardization of instantaneous fluoroprobe measurements of benthic algal biomass and composition in streams

Fluoroprobes, such as BenthoTorch, offer a relatively rapid in situ method for monitoring benthic algae, provide new opportunities for aquatic ecological research, and enable early warning of algal proliferation in municipal water supplies. Currently, however, BenthoTorch is limited for the measurement of heterogeneous samples, and homogenizing samples is rather difficult. In this study, we compared chlorophyll-a (Chl-a) measurements between BenthoTorch and standard laboratory methods to quantify and describe the biomass and biovolume proportion of benthic algae growing on artificial and natural substrates. We used the difference in Chl-a measurements between these methods (n = 359) to evaluate the effects of environmental variables. Moreover, we used artificial and natural substrates to determine whether either of them reduced variation in BenthoTorch measurements. There was a general concordance in measurements between the two methods, but this agreement was stronger for artificial substrates. Artificial substrates also led to significantly less variation in BenthoTorch readings compared with natural substrates. This may be attributed to the formation of relatively thin algal mats on artificial substrates. To enable early warning of algal proliferation in an aquatic ecosystem, we recommend the use of BenthoTorch and artificial substrates combined with appropriate calibration using standard laboratory methods. The ability of BenthoTorch to produce instantaneous results facilitates replicate collection, which reduces sampling error and increases sampling area on the same day. Despite substantial variation in readings on natural substrates, BenthoTorch enables relatively rapid measurements, facilitating easy monitoring of large areas. Therefore, BenthoTorch may be worth incorporating into aquatic ecosystem studies, depending on the specific research questions.

Minimizing heterogeneity of VOS observations for improving estimates of short-wave radiation over the oceans

The paper describes the development of climatologies of short-wave radiation over the ocean using visually observed cloud cover from the International Comprehensive Ocean-Atmosphere Data Set (ICOADS). For producing climatology of short-wave radiation, we applied bulk parameterization (known as SAIL/IOARAS). For a proper computation of short-wave radiation values special effort was taken to reduce sampling errors in cloud cover from ICOADS. Specifically, we consider the uncertainties associated with temporal inhomogeneity of observations and potentially implying biases in short-wave radiation estimates related to the astronomy factors critical for short-wave radiation. For this purpose, we propose simple and effective algorithms.

Diagnostic Discordance in Intraoperative Frozen Section Diagnosis of Ovarian Tumors: A Literature Review and Analysis of 871 Cases Treated at a Japanese Cancer Center

This study examined the accuracy and pitfalls associated with frozen section diagnosis of primary ovarian tumors and ovarian metastases based on the 2014 World Health Organization classification (WHO) criteria and proposed improvements from a pathologist's perspective. We microscopically reviewed 871 cases of primary ovarian tumor (N = 802) and ovarian metastasis (N = 69) and compared the results of frozen sections with the final diagnosis. Malignant potential concordance (benign, borderline, or malignant) and specific discordant diagnosis rates were analyzed. Finally, we conducted a unique literature review of specific diagnostic errors in the frozen section diagnosis of primary ovarian tumors. Of 802 primary ovarian tumors, 50 (6.2%) cases showed discordant diagnoses in which mucinous carcinoma (40.5%), low-grade serous carcinoma (LGSC; 31.3%), and mucinous borderline tumor (18.4%) were frequently misinterpreted. Of 69 ovarian metastases, all 4 cases of low-grade appendiceal mucinous neoplasm (LAMN) were misdiagnosed as primary ovarian mucinous tumor. A literature review revealed that mucinous/serous borderline tumor or carcinoma accounted for approximately 70% of 217 reported discordant diagnoses. In the present study, the concordance rate of malignant potential of the tumor was comparable to that previously reported. Even in the 2014 WHO classification, primary ovarian mucinous borderline tumor/carcinoma and LGSC still comprised the majority of discordant cases. Grossing methods that reduce sampling error are required. LAMN was frequently misinterpreted as a benign or borderline ovarian mucinous tumor. To prevent this error, a differential algorithm integrating clinical information and gross findings should be developed.

Electroanatomic mapping-guided endomyocardial biopsy in patients with apparently idiopathic ventricular arrhythmias.

The management of ventricular arrhythmias (VA) in the presence of an apparently normal heart represents a major clinical challenge and a main field of clinical research. In the past years, new imaging techniques and the spreading of new generation genetic testing have improved our knowledge of the pathogenesis of apparently idiopathic VA. However, in the absence of specific recommendations, the type and the number of noninvasive and invasive studies necessary to rule out a possible underlying cause of VA or sudden cardiac death remain extremely variable. Therefore, in many patients the underlying cardiac disease is not recognized, and a possible specific therapeutic approach cannot be initiated. Endomyocardial biopsy (EMB) can provide a significant contribution to the identification of myocardial disorders causing VA but has never been definitively included in the routine diagnostic work-up of these patients due to the possible sampling error particularly in disorders with a focal or patchy distribution. Three-dimensional electroanatomic mapping (EAM) may guide EMB allowing to draw myocardial samples from abnormal voltage, areas of the ventricular wall, thus reducing sampling error and increasing the sensitivity of EMB. The systematic association of EAM with EMB represents a crucial approach to characterize the pathological substrate of electroanatomic abnormalities and VA and to further clarify the arrhythmogenic mechanisms of acquired and also inherited arrhythmic disorders.

Unbiased corneal tissue analysis using Gabor-domain optical coherence microscopy and machine learning for automatic segmentation of corneal endothelial cells.

.Significance: An accurate, automated, and unbiased cell counting procedure is needed for tissue selection for corneal transplantation.Aim: To improve accuracy and reduce bias in endothelial cell density (ECD) quantification by combining Gabor-domain optical coherence microscopy (GDOCM) for three-dimensional, wide field-of-view () corneal imaging and machine learning for automatic delineation of endothelial cell boundaries.Approach: Human corneas stored in viewing chambers were imaged over a wide field-of-view with GDOCM without contacting the specimens. Numerical methods were applied to compensate for the natural curvature of the cornea and produce an image of the flattened endothelium. A convolutional neural network (CNN) was trained to automatically delineate the cell boundaries using 180 manually annotated images from six corneas. Ten additional corneas were imaged with GDOCM and compared with specular microscopy (SM) to determine performance of the combined GDOCM and CNN to achieve automated endothelial counts relative to current procedural standards.Results: Cells could be imaged over a larger area with GDOCM than SM, and more cells could be delineated via automatic cell segmentation than via manual methods. ECD obtained from automatic cell segmentation of GDOCM images yielded a correlation of 0.94 () with the manual segmentation on the same images, and correlation of 0.91 () with the corresponding manually counted SM results.Conclusions: Automated endothelial cell counting on GDOCM images with large field of view eliminates selection bias and reduces sampling error, which both affect the gold standard of manual counting on SM images.

Sampling errors arising from carousel entrainment and insufficient flushing of oceanographic sampling bottles

AbstractCollection of representative water samples is necessary for limnology and oceanography. Unfortunately, some common sampling practices using current technology have the potential to introduce significant sampling errors. For example, modern carousel hardware and software can permit closing of sampling bottles as soon as the bottle reaches the desired depth rather than allowing sufficient time (i.e., soak time) for ambient water to flush the sampling bottles. The large size of many conductivity–temperature–depth (CTD)/carousels and their associated instrumentation also increase the impacts of water entrainment as the equipment travels within the water column. Finally, some modern sampling bottles have small openings relative to their volumes, a factor that inhibits bottle flushing, particularly if the bottle closures are not completely open. Inspection of data from selected research cruises suggests that insufficient soak times can produce biased water samples. In this study, we undertook field experiments that help to quantify the errors that can arise from CTD carousel entrainment and insufficient bottle flushing. The experiments demonstrate that under stratified conditions, soak times of more than 2 min may be required to collect representative water samples. The experiments also demonstrate the occurrence of stratification within sample bottles. Some protocols that may reduce sampling errors are suggested.

Mitigating occlusion effects in Leaf Area Density estimates from Terrestrial LiDAR through a specific kriging method

Terrestrial Laser Scanning (TLS) has been used during the past decade to capture the complexity of 3D forest canopy structures, especially Leaf or Plant Area Density (LAD/PAD). TLS data, i.e. point cloud, can be divided into voxels to estimate the three-dimensional distribution of LAD/PAD. However, the combination effects of vegetation occlusion and shooting pattern of TLS scanners lead to a highly heterogeneous sampling, which limits the reliability of some local estimates, since several voxels are either not explored or poorly-explored by laser beams. In practice, recommendations vary regarding the minimum number of beams crossing voxels or the minimum path lengths required to provide reliable predictions. In addition, assigning a value to non-explored and poorly-explored voxels is still an open question.The present work proposes a new method, called LAD-kriging, to mitigate the impact of non-uniform sampling and to increase the accuracy of LAD estimates in non-explored and poorly-explored voxels. The method takes advantage of i) an unbiased LAD estimator of known variance, which was recently developed; ii) the spatial correlation of the LAD field, which derives from vegetation clumping. LAD-kriging computes kriging weights from mathematical derivations, which takes into account both spatial dependencies in the LAD field and the reliability of the estimate available in each voxel. It was evaluated through numerical experiments, which enabled to validate the algorithm and to evaluate its performance through comparison with true references. An example application to field data shows that such spatial correlations truly exist in the field and that LAD-kriging entails to reduce sampling errors (with respect to full resolution scanning). Although a real validation is impossible due to the lack of precise references at the voxel scale, this example allows to gain confidence for its application to field data.In our realistic numerical experiment, up to 25–30% of voxels can be explored by <100 beams, thereby leading to unreliable estimates of the LAD within these voxels and frequent large local errors. In cases where voxels were not explored at all, simple methods previously reported in earlier studies, such as ignoring occlusion or assigning “mean layer” values to unexplored voxels were inefficient (RMSE = 0.72 m−1 and poor local accuracy). By contrast, LAD-kriging exhibited the smallest errors (RMSE = 0.48 m−1) and was locally more accurate. LAD-Kriging was also efficient for correcting voxels explored with few beams, i.e. unreliable, dropping RMSE from 0.92 to 0.42 m−1 in these volumes. In practice, LAD-Kriging does not require defining a reliability threshold or any arbitrary parameterization, which is convenient for field applications and can be extended to other applications than LAD with TLS, such as UAS/VAS scanning, provided that unbiased estimators of known variance are available.

How large are temporal representativeness errors in paleoclimatology?

Abstract. Ongoing work in paleoclimate reconstruction prioritizes understanding the origins and magnitudes of errors that arise when comparing models and data. One class of such errors arises from assumptions of proxy temporal representativeness (TR), i.e., how accurately proxy measurements represent climate variables at particular times and time intervals. Here we consider effects arising when (1) the time interval over which the data average and the climate interval of interest have different durations, (2) those intervals are offset from one another in time (including when those offsets are unknown due to chronological uncertainty), and (3) the paleoclimate archive has been smoothed in time prior to sampling. Because all proxy measurements are time averages of one sort or another and it is challenging to tailor proxy measurements to precise time intervals, such errors are expected to be common in model–data and data–data comparisons, but how large and prevalent they are is unclear. This work provides a 1st-order quantification of temporal representativity errors and studies the interacting effects of sampling procedures, archive smoothing, chronological offsets and errors (e.g., arising from radiocarbon dating), and the spectral character of the climate process being sampled. Experiments with paleoclimate observations and synthetic time series reveal that TR errors can be large relative to paleoclimate signals of interest, particularly when the time duration sampled by observations is very large or small relative to the target time duration. Archive smoothing can reduce sampling errors by acting as an anti-aliasing filter but destroys high-frequency climate information. The contribution from stochastic chronological errors is qualitatively similar to that when an observation has a fixed time offset from the target. An extension of the approach to paleoclimate time series, which are sequences of time-average values, shows that measurement intervals shorter than the spacing between samples lead to errors, absent compensating effects from archive smoothing. Nonstationarity in time series, sampling procedures, and archive smoothing can lead to changes in TR errors in time. Including these sources of uncertainty will improve accuracy in model–data comparisons and data comparisons and syntheses. Moreover, because sampling procedures emerge as important parameters in uncertainty quantification, reporting salient information about how records are processed and assessments of archive smoothing and chronological uncertainties alongside published data is important to be able to use records to their maximum potential in paleoclimate reconstruction and data assimilation.

AUXILIARY SAMPLING TECHNOLOGY AND SYSTEM FOR MASS SURVEYING AND MAPPING RESULTS ORIENTED TO QUALITY INSPECTION GOALS

Abstract. Based on the requirements of quality supervision inspection for national surveying and mapping, this paper has carried out research on sampling and auxiliary sampling technology and sampling system for quality inspection targets for different objects and different types of surveying results. The study designed the quantitative random sampling scheme of the random inspection objects considering the principle of supervision and spot check of surveying and mapping quality. It also designed the stratification scheme of surveying and mapping results under different quality inspection targets and object conditions, and the stratified adjustment scheme with prior quality information. Based on the above scheme, the national surveying and mapping supervision inspection sampling system based on the project rolling pool and the stratified random auxiliary sampling prototype system for the quality inspection target of surveying and mapping results are implemented. In recent years, they have been widely used in the national surveying and mapping geographic information supervision inspection and surveying and mapping results quality inspection, which guaranteed the scientific and reasonable determination of surveying and mapping quality supervision inspection objects, and solved problems in the quality inspection of surveying results, such as unreasonable stratification in manual sampling, and inevitable error in random sampling. This is of great significance for further improving sampling efficiency, reducing sampling error, reducing sampling risk, and promoting informatization of quality inspection.

Intraoperative Molecular Imaging for ex vivo Assessment of Peripheral Margins in Oral Squamous Cell Carcinoma.

Objective: Complete surgical resection is the standard of care for treatment of oral cancer although the positive margin rate remains 15–30%. Tissue sampling from the resected specimen and from the wound bed for frozen section analysis (FSA) remains the mainstay for intraoperative margin assessment but is subject to sampling error and can require the processing of multiple samples. We sought to understand if an ex vivo imaging strategy using a tumor-targeted fluorescently labeled antibody could accurately identify the closest peripheral margin on the mucosal surface of resected tumor specimen, so that this “sentinel margin” could be used to guide pathological sampling.Materials and Methods: Twenty-nine patients with oral squamous cell carcinoma scheduled for surgical resection were consented for the study and received systemic administration of a tumor-targeted fluorescently labeled antibody (Panitumumab IRDye800CW). After surgical resection, the tumor specimen was imaged using a closed-field fluorescent imaging device. Relevant pathological data was available for five patients on retrospective review. For each of these five patients, two regions of highest fluorescence intensity at the peripheral margin and one region of lowest fluorescence intensity were identified, and results were correlated with histology to determine if the region of highest fluorescence intensity along the mucosal margin (i.e., the sentinel margin) was truly the closest margin.Results: Imaging acquisition of the mucosal surface of the specimen immediately after surgery took 30 s. In all of the specimens, the region of highest fluorescence at the specimen edge had a significantly smaller margin distance than other sampled regions. The average margin distance at the closest, “sentinel,” margin was 3.2 mm compared to a margin distance of 8.0 mm at other regions (p < 0.0001).Conclusions: This proof-of-concept study suggests that, when combined with routine FSA, ex vivo fluorescent specimen imaging can be used to identify the closest surgical margin on the specimen. This approach may reduce sampling error of intraoperative evaluation, which should ultimately improve the ability of the surgeon to identify the sentinel margin. This rapid sentinel margin identification improves the surgeon's orientation to areas most likely to be positive in the surgical wound bed and may expedite pathology workflow.

Optical coherence angiography for pre-treatment assessment and treatment monitoring following photodynamic therapy: a basal cell carcinoma patient study

Microvascular networks of human basal cell carcinomas (BCC) and surrounding skin were assessed with optical coherence angiography (OCA) in conjunction with photodynamic therapy (PDT). OCA images were collected and analyzed in 31 lesions pre-treatment, and immediately/24 hours/3–12 months post-treatment. Pre-treatment OCA enabled differentiation between prevalent subtypes of BCC (nodular and superficial) and nodular-with-necrotic-core BCC subtypes with a diagnostic accuracy of 78%; this can facilitate more accurate biopsy reducing sampling error and better therapy regimen selection. Post-treatment OCA images at 24 hours were 98% predictive of eventual outcome. Additional findings highlight the importance of pre-treatment necrotic core, vascular metrics associated with hypertrophic scar formation, and early microvascular changes necessary in both tumorous and peri-tumorous regions to ensure treatment success.

Probe-based fluorescence dosimetry of an antibody-dye conjugate to identify head and neck cancer as a first step to fluorescence-guided tissue preselection for pathological assessment.

Despite the rapid growth of fluorescence imaging, accurate sampling of tissue sections remains challenging. Development of novel technologies to improve intraoperative assessment of tissue is needed. A novel contact probe-based fluorescence dosimeter device, optimized for IRDye800CW quantification, was developed. After evaluation of the device in a phantom setup, its clinical value was defined ex vivo in patients with head and neck squamous cell carcinoma who received panitumumab-IRDye800CW. Ten patients were enrolled with a total of 216 data points obtained. Final histopathology showed tumor in 119 spots and normal tissue in 97 spots. Fluorescence-to-excitation ratios in tumor tissue were more than three times higher than those in normal tissue. The area under the curve was 0.86 (95% CI: 0.81-0.91) for tumor detection. Fluorescence-guided tissue preselection using a fluorescence dosimeter could have substantial impact on tissue sampling for frozen section analysis and potentially reduce sampling errors.

Endoscopists systematically undersample patients with long-segment Barrett’s esophagus: an analysis of biopsy sampling practices from a quality improvement registry

Guidelines recommend systematic biopsy sampling in Barrett's esophagus (BE) to reduce sampling error. Adherence to this biopsy sampling protocol has been suggested as a quality indicator; however, estimates of adherence are not available. Using a national registry, we assessed adherence and identified predictors of adherence to biopsy sampling protocols. We analyzed data from the GI Quality Improvement Consortium Registry that included procedure indication, demographics, endoscopy, and pathology results. Patients with an indication of BE screening/surveillance or an endoscopic finding of BE were included. Adherence to the Seattle protocol was assessed by dividing BE length by number of pathology jars, with a ratio≤2.0 with rounding down (lenient definition) or rounding up (stringent definition) for odd BE lengths considered adherent. Variables associated with adherence were assessed using generalized estimating equations to control for clustering within individual physicians. Of 786,712 EGDs assessed, 58,709 (7.5%) EGDs in 53,541 patients met inclusion criteria (mean age, 61.3 years; 60.4% men; 90.2% white; mean BE length, 2.3 cm). When the lenient and stringent definitions for adherence were used, 87.8% and 82.7% of EGDs were adherent, respectively. Increasing BE length was the most significant predictor of nonadherence (odds ratio, .69; 95% confidence interval, .67-.71). Other predictors were increasing age, male gender, increasing American Society of Anesthesiologists class, and practice location. Performance of EGD by nongastroenterologist physicians was associated with nonadherence (odds ratio, .07; 95% confidence interval, .06-.10). Nearly 20% of endoscopies performed in BE patients were not adherent to the Seattle protocol. As BE length increases, endoscopists become less compliant with odds of nonadherence increasing by 31% with every 1-cm increase in length.

Integrating the Theory of Sampling into Underground Mine Grade Control Strategies: Case Studies from Gold Operations

Grade control aims to deliver adequately defined tonnes of ore to the process plant. The foundation of any grade control programme is collecting high-quality samples within a geological context. The requirement for quality samples has long been recognised, in that these should be representative and fit-for-purpose. Correct application of the Theory of Sampling reduces sampling errors across the grade control process, in which errors can propagate from sample collection through sample preparation to assay results. This contribution presents three case studies which are based on coarse gold-dominated orebodies. These illustrate the challenges and potential solutions to achieve representative sampling and build on the content of a previous publication. Solutions ranging from bulk samples processed through a plant to whole-core sampling and assaying using bulk leaching, are discussed. These approaches account for the nature of the mineralisation, where extreme gold particle-clustering effects render the analysis of small-scale samples highly unrepresentative. Furthermore, the analysis of chip samples, which generally yield a positive bias due to over-sampling of quartz vein material, is discussed.

A double instrumental variable method for geophysical product error estimation

The global validation of remotely sensed and/or modeled geophysical products is often complicated by a lack of suitable ground observations for comparison. By cross-comparing three independent collocated observations, triple collocation (TC) can solve for geophysical product errors in error-prone systems. However, acquiring three independent products for a geophysical variable of interest can be challenging. Here, a double instrumental variable based algorithm (IVd) is proposed as an extension of the existing single instrumental variable (IVs) approach to estimate product error standard deviation (σ) and product-truth correlation (R) using only two independent products - an easier requirement to meet in practice. An analytical examination of the IVd method suggests that it is less prone to bias and has reduced sampling errors relative to IVs. Results from an example application of the IVd method to precipitation product error estimation show that IVd-based σ and R are good approximations of reference values obtained from TC at the global extent. In addition to their spatial consistency, IVd estimated error metrics also have only marginal (less than 5%) relative biases versus a TC baseline. Consistent with our earlier analytical analysis, these empirical results are shown to be superior to those obtained by IVs. However, several caveats for the IVd approach should be acknowledged. As with TC and IVs, IVd estimates are less robust when the signal-to-noise ratio of geophysical products is very low. Additionally, IVd may be significantly biased when geophysical products have strongly contrasting error auto-correlations.

Toward Opportunistic Compression and Transmission for Private Car Trajectory Data Collection

The advances in vehicle location service and communication techniques have generated massive spatial-temporal trajectory data, which has caused the crises of storage and communication in the vehicle trajectory data center. In this paper, we propose a novel opportunistic compression and transmission-based long short-term memory method, namely, OCT-LSTM, with aims of reducing trajectory transmission overhead and storage cost. We first present a low-cost vehicle location device for trajectory real-time collection of private cars. Within the proposed OCT-LSTM, we introduced a map-matching method based on MIV-matching which reduces sampling errors of raw trajectories. Then, we present a spatial-temporal transformation method to divide the trajectory data into two parts, i.e., spatial path and time-distance parts, and realize the compression operation separately. Similar movement patterns are repeated and randomly present in trajectories of private cars. In this paper, we train the LSTM model to remember and predict these repetitive movement patterns through historical trajectories. An opportunistic transmission of trajectory data from the vehicle terminal to the data center was designed, which can dramatically decrease the transmission overhead. The proposed OCT-LSTM not only realizes real-time trajectory preprocessing and compressing but also ensures high trajectory compression ratio. To validate the performance of the OCT-LSTM, we collect a large-scale private car trajectory data from real urban environments. The experiments verify the compression ratio effectiveness and time-delay superiority of the proposed methods.

Environmental Assessment in Neotropical Watersheds: A Multi-Factorial Approach

This study evaluated the environmental conditions of two watersheds selected on the basis of similarities in land use. The environmental conditions of the watersheds were analyzed using two geoprocessing methods and in situ evaluations by applying the rapid assessment protocol (RAP). Geospatial image processing was used to analyze land use, slope, soil classification, and rainfall, while RAP was used to evaluate the connectivity and size of riparian corridors. The results revealed varied uses of land with the landscape matrix in both watersheds, composed of agriculture, pasture, and urban centers. Urban centers were defined as spots and riparian zones as corridors. The analysis of environmental fragility considering all the geospatial variables, classified both watersheds as having medium fragility. The most fragile sites were the urban centers, which had a high slope and degraded riparian zone. Onsite assessments have shown that corridors do not have the size required by legislation; they are fragmented and unstructured, and they contain exotic species. We also propose that a multi-factorial approach be used to evaluate watersheds, associating geospatial assessments and onsite analyses that consider the limitations pointed out in each protocol. This reduces sampling errors and shows the actual state of conservation in riparian zones.