Com o advento da tecnologia de mapeamento por sensoriamento remoto com Aeronaves Remotamente Pilotadas (RPA) popularmente conhecidos como drones, aliada ao sistema Global Navigation Satellite System ...(GNSS), ferramenta utilizada para o posicionamento de pontos de apoio terrestre, georreferenciados em tempo real, tornou-se um recurso promissor na detecção do uso e cobertura do solo. Neste sentido o presente trabalho apresenta um estudo para avaliar a exatidão cartográfica para levantamentos planimétricos e cadastral do Núcleo Avançado do Pantanal (NAPAN) situado no município de Poconé - MT. Para avaliar a qualidade do mapeamento, o Padrão de Exatidão Cartográfica (PEC) será analisado com base no Decreto-Lei 89.817, regulador das Normas Técnicas da Cartografia Nacional. A exatidão temática através de análises estatísticas por meio de índices não espaciais extraídos da Matriz de Erros (ME) gerada pela classificação supervisionada da imagem. O projeto foi dividido em 5 fases: (a) Levantamento de pontos de controle de alta precisão na área de estudo com receptores GNSS, (b) Aerolevantamento com drone, (c) Geração do ortomosaico, (d) Classificação do uso e cobertura do solo e (e) Análises do PEC e dos índices de concordância temáticos Kappa e Global. Foi obtido um ortomosaico com resolução espacial de 2,12 cm/pixel, classificado na classe A e escala de 1/1000, bem como a exatidão Global do uso e ocupação do solo de 0,91 e índice Kappa de 0,88, permitindo maior qualidade posicional do ortomosaico e uma excelente acurácia na classificação do uso da Terra.Palavras-Chave: Sensoriamento Remoto, GNSS, ArcGis, Índice Kappa
The crisis in traditional forest and farming activities that began in the second half of the 20th century has given way to a new territorial structure, characterised by greater forest density and an ...acceleration of urban sprawl, which has affected the impact of fires on the territory and especially on the inhabitants. The increased vulnerability of homes located at the wildland-urban interface (WUI) and the differences in the intensity of fire impact makes it necessary to identify different typologies of WUI zones. Characterization of WUI typologies was based on four forest fires with distinct characteristics, selected from fires that occurred in Catalonia in 2003 and 2012. Based on the different landscape units that have been studied and the dynamics of the changes that have occurred in the study area over the past 15 years, together with the occurrence of fires during this period, identified three major WUI zone typologies: a) metropolitan, b) agroforest and c) mountain agrosilvopastoral. The results, based on Kappa index and Rate of Change, show significant changes in Land Use and Land Cover between 2003 and 2009 in each study area, but the economic and social context in each region generated different territorial dynamics for each typology. This diagnosis contributes to knowledge that expands the available planning and management tools to mitigate the effects of wildfires.
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•LULCC have led to different intensities in WUI fire vulnerability in Catalonia.•To identify land use change is a key to understanding the dynamics of land covers.•The abandonment of traditional activities negatively affected WUI vulnerability.•The diagnostic analysis contributes to the knowledge to preventing wildfires.•We need to adapt prevention tools according to different landscape vulnerability.
Cerebrospinal fluid (CSF) free light chains (FLC) may be an alternative biomarker to oligoclonal bands (OCB) in multiple sclerosis (MS). Herein, we compared the diagnostic accuracy of CSF OCB and FLC ...and we tested the prognostic value of FLC in a cohort of 64 MS patients and 106 controls. A κ-index >7.83 was more sensitive but less specific than OCB in discriminating MS patients from controls. Additionally, a κ-index >10.61 performed better than OCB in the discrimination between MS and controls with inflammatory neurological diseases (p < .001). In clinically isolated syndrome (CIS) patients, a κ-index >10.61 significantly predicted time to conversion to MS (p = .020). κ-index might be a valid alternative to OCB as a diagnostic biomarker for MS and might also be a prognostic marker in CIS.
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•κ-index is more sensitive and less specific than OCB for MS diagnosis.•κ-index performs better than OCB in discriminating MS from other inflammatory neurological diseases.•κ-index correlates with different disease characteristics in MS.•κ-index predicts disease activity in early MS patients.
This study investigates how effective the receiver operating characteristic (ROC) curve is for comparing the reliability of landslide susceptibility maps (LSMs). In this regard, we selected a basin ...prone to landslides in northern Iran and employed frequency ratio and weight-of-evidence methods for modelling. Modelling for each method was done by considering three fractions of training/test landslides (50/50, 60/40, and 70/30) and, in addition, three random seeds for each of these fractions, leading to produce 18 LSMs. Validation rates of LSMs were obtained through calculation of the area under the ROC curve. Moreover, Cohen's kappa index was calculated to reveal the magnitude of the agreement between the maps. Results showed that all LSMs, despite having equal validation rates, were considerably different in terms of spatial prediction pattern. It is concluded that, although as a prevalent validation tool, ROC curve is only an indicator of the general reliability of geographical prediction maps and cannot reveal the uncertainty of spatial prediction patterns. Therefore, to reduce the conflicts between the maps and create a single reliable map, all LSMs were merged using the overlaying statistical functions that can extract the best possible zone pattern from all the overlapped patterns.
Evaluation of Community Detection Methods Liu, Xin; Cheng, Hui-Min; Zhang, Zhong-Yuan
IEEE transactions on knowledge and data engineering,
09/2020, Letnik:
32, Številka:
9
Journal Article
Recenzirano
Odprti dostop
Community structures are critical towards understanding not only the network topology but also how the network functions. However, how to evaluate the quality of detected community structures is ...still challenging and remains unsolved. The most widely used metric, normalized mutual information (NMI), was proven to have finite size effect, and its improved form relative normalized mutual information (rNMI) has reverse finite size effect. Corrected normalized mutual information (cNMI) was thus proposed and has neither finite size effect nor reverse finite size effect. However, in this paper, we show that cNMI violates the so-called proportionality assumption. In addition, NMI-type metrics have the problem of ignoring importance of small communities. Finally, they cannot be used to evaluate a single community of interest. In this paper, we map the computed community labels to the ground-truth ones through integer linear programming, and then use kappa index and F-score to evaluate the detected community structures. Experimental results demonstrate the advantages of our method.
Background
Interferon‐gamma (IFN‐γ) release assays (IGRAs) are useful for the assessment of the T‐cell response to severe acute respiratory syndrome‐coronavirus‐2 (SARS‐CoV‐2). We aimed to assess the ...performance of the newly developed IGRA ELISA test compared to the pre‐existing assays and to validate the cutoff value in real‐world conditions.
Methods
We enrolled 219 participants and assessed agreement between STANDARD‐E Covi‐FERON ELISA with Quanti‐FERON SARS‐CoV‐2 (QFN SARS‐CoV‐2), as well as with T SPOT Discovery SARS‐CoV‐2 based on Cohen's kappa‐index. We further determined the optimal cutoff value for the Covi‐FERON ELISA according to the immune response to vaccinations or infections.
Results
We found a moderate agreement between Covi‐FERON ELISA and QFN SARS‐CoV‐2 before vaccination (kappa‐index = 0.71), whereas a weak agreement after the first (kappa‐index = 0.40) and second vaccinations (kappa‐index = 0.46). However, the analysis between Covi‐FERON ELISA and T SPOT assay demonstrated a strong agreement (kappa‐index >0.7). The cut‐off value of the OS (original spike) marker was 0.759 IU/mL with a sensitivity of 96.3% and specificity of 78.7%, and that of the variant spike (VS) marker was 0.663 IU/mL with a sensitivity and specificity of 77.8% and 80.6%, respectively.
Conclusion
The newly determined cut‐off value may provide an optimum value to minimize and prevent the occurrence of false‐negative or false‐positive during the assessment of T‐cell immune response using Covi‐FERON ELISA under real‐world conditions.
The presence of IFN‐γ in the patient's blood samples can be an indicator of SARS‐CoV‐2 infection or the development of cellular immune response following the COVID‐19 vaccination. An IFN‐γ release assay (IGRA) enables the detection of IFN‐γ in the blood, and, therefore, plays an important role in the detection of SARS‐CoV‐2 or confirmation of the COVID‐19 vaccine's efficacy. Subsequently, an optimum cutoff value of the IGRA's markers is crucial to determine the accuracy of the IGRA test in discriminating the presence or absence of IFN‐γ in the blood samples.
Statistical independence test and validity of the CA (Cellular Automata) Markov process for projecting future land use and land cover (LULC) changes were carried out in this study. Predicting ...quantity and location changes have been analyzed, and statistically evaluated. Validity of the CA Markov process has been examined using various Kappa Index of Agreement (KIA or Kstandard) and related statistical variations on the KIA. Statistical test of independence (K2) was performed and markovian suitability has been checked using hypothesis of goodness of fit (Xc2). Hypothesis of statistical independence was rejected, which proved that land use land cover change trends are similar like previous development of land. With acceptance of the hypothesis of goodness of fit (Xc2) proved that actual transition probability of matrix is fitted with expected transition probability prepared using Markov chain method. Statistics indicates Kno, Klocation, Klocation Strata and Kstandard are 0.8347, 0.859, 0.8591 and 0.7928, respectively.
Landslides are one of the most frequent geomorphic hazards, and they often result in the loss of property and human life in the Changbai Mountain area (CMA), Northeast China. The objective of this ...study was to produce and compare landslide susceptibility maps for the CMA using an information content model (ICM) with three knowledge-driven methods (the artificial hierarchy process with the ICM (AHP-ICM), the entropy weight method with the ICM (EWM-ICM), and the rough set with the ICM (RS-ICM)) and to explore the influence of different knowledge-driven methods for a series of parameters on the accuracy of landslide susceptibility mapping (LSM). In this research, the landslide inventory data (145 landslides) were randomly divided into a training dataset: 70% (81 landslides) were used for training the models and 30% (35 landslides) were used for validation. In addition, 13 layers of landslide conditioning factors, namely, altitude, slope gradient, slope aspect, lithology, distance to faults, distance to roads, distance to rivers, annual precipitation, land type, normalized difference vegetation index (NDVI), topographic wetness index (TWI), plan curvature, and profile curvature, were taken as independent, causal predictors. Landslide susceptibility maps were developed using the ICM, RS-ICM, AHP-ICM, and EWM-ICM, in which weights were assigned to every conditioning factor. The resultant susceptibility was validated using the area under the ROC curve (AUC) method. The success accuracies of the landslide susceptibility maps produced by the ICM, RS-ICM, AHP-ICM, and EWM-ICM methods were 0.931, 0.939, 0.912, and 0.883, respectively, with prediction accuracy rates of 0.926, 0.927, 0.917, and 0.878 for the ICM, RS-ICM, AHP-ICM, and EWM-ICM, respectively. Hence, it can be concluded that the four models used in this study gave close results, with the RS-ICM exhibiting the best performance in landslide susceptibility mapping.
En este estudio se evaluó la cobertura boscosa en la subcuenca del río Yuracyacu durante el periodo 1989-2010. Para esto se utilizaron 6 imágenes satelitales Landsat del sensor Thematic Mapper de los ...años 1989, 1995, 2001, 2006, 2008, 2010, sobre las cuales se realizaron los respectivos procesamientos utilizando CLASlite mediante el análisis de la cobertura fraccional. Durante el periodo 1989-1995 se obtuvo una pérdida de 18.2 km2 de la cobertura boscosa, para el periodo 1995-2001 la cobertura boscosa fue recuperada con una tasa de 1.2 km2/año; para los periodos 2001-2006, 2006-2008 y 2008-2010 se evidenciaron los progresivos retrocesos del bosque húmedo tropical, siendo estos 8.9 km2, 3.4 km2 y 7.5 km2, respectivamente. En los 21 años se han perdido 32 km2 de bosque tropical amazónico de la subcuenca con una tasa de deforestación -1.2% anual; la tasa de deforestación más alta se encontró en el periodo 1989-1995 y fue -2.27%. El modelo para determinar escenarios futuros de bosque tropical en la subcuenca estimó un área resultante de 89.1 km2 para el año 2030, demostrando la progresiva disminución de bosque húmedo tropical. Finalmente, en la validación de los resultados se obtuvo una fiabilidad global igual a 85% y un índice de Kappa de 0.65 indicando la bondad y precisión de la clasificación. Los resultados de este estudio permitirán orientar acciones para la conservación y manejo del bosque húmedo tropical de la subcuenca.
•KFLC can be determined in CSF samples by sensitive automated methods.•Several neuro-inflammatory conditions that can mimic MS were included as controls.•Most MS cases showed K index ≥ 7.25, ...including some cases with negative OCBs.•K index can provide valuable support to the analysis of OCB results.•Selecting samples for OCB detection can improve analytical workflow (K index ≥ 2.55)
Automated, technically simple analytical methods offering objective results are highly valued in clinical laboratories. Kappa free light chains (KFLC) in cerebrospinal fluid (CSF) are promising multiple sclerosis (MS) biomarkers, particularly kappa (K) index.
KFLC were determined in CSF and serum samples of patients diagnosed with MS, clinically/radiologically isolated syndrome (N, 39), and controls (N, 152; inflammatory and non-inflammatory neurological disorders). Diagnostic performance of several KFLC parameters, previously determined oligoclonal band (OCB) testing, and IgG index, was assessed. A K index decision threshold for sample screening was identified and reduction in performed OCB analyses estimated accordingly.
Higher KFLC parameters were detected in the MS group and K index performed best among them (AUC 0.92). At a 7.25 cut-off it showed better sensitivity (85% vs. 77%) though less specificity (88% vs. 91%) than OCBs. Comparatively, IgG index’s performance was inferior (AUC 0.83). A decision K index threshold of 2.55 (97% sensitivity) would reduce OCB testing by 52% in the studied population.
The proposed 7.25 cut-off could assist MS diagnostics and identify some false negative cases from OCB studies. Sequential algorithms using K index for the decision to perform OCB detection would improve laboratory efficiency and substantially reduce costs.
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