Extraction of forest plantation extents using majority voting classification fusion algorithm

© 2018 Proceedings - 39th Asian Conference on Remote Sensing: Remote Sensing Enabling Prosperity, ACRS 2018 Satellite Phased Array L-band Synthetic Aperture Radar-2 has great advantages in extracting natural and industrial forest plantation in tropical areas, but it suffers from presence of speckle that create problem to identify the forest body. Optimal fusion of Landsat-8 operational land imager bands with ALOS PALSAR-2 can provide the ideal complementary information for an accurate forest extraction while suppressing unwanted information. The goal of this study is to analyze the potential ability of Landsat-8 OLI and ALOS PALSAR-2 as complementary data resources in order to extract land cover especially forest types. Comprehensive preprocessing analysis (e.g. geometric correction, filtering enhancement and polarization combination) were conducted on ALOS PALSAR-2 dataset in order to make the imagery ready for processing. Principal component index method as one of the most effective Pan-Sharpening fusion approaches was used to synthesize Landsat and ALOS PALSAR-2 images. Three different classifiers methods (support vector machine, k-nearest neighborhood, and random forest) were employed and then fused by majority voting algorithm to generate more robust and precise classification result. Accuracy of the final fused result was assessed on the basis of ground truth points by using confusion matrices and kappa coefficient. This study proves that the accurate and reliable majority voting fusion method can be used to extract large-scale land cover with emphasis on natural and industrial forest plantation from synthetic aperture radar and optical datasets

Study of Causes, Methods and Complications of Early and Late Miscarriage due to Intentional Abortion in Women referred to Health Centers covered by Shahid Beheshti University

Abstract Introduction: Induced abortion is a major threat to women’s fertility health. In particular, in developing countries and the societies where abortion is illegal, abortions are commonly carried out under unsanitary conditions, causing maternal complications, dangers to maternal health, and women’s future infertility. These consequences are especially evident in Iran where at least 80,000 illegal abortions are done annually. The current study aimed to examine the reasons for abortion, methods of abortion, and its short-term and long-term complications. Methods: This study, which adopted a descriptive design, was conducted among the women who had already carried out abortion and referred to one of the health, therapeutic, and educational centers affiliated with Shahid Beheshti University of Medical Sciences. The participants (N = 360) were selected the data were gleaned through a self-designed questionnaire and statistically analyzed using SPSS version 17. Results: The results of analyzing the data collected through the 369 questionnaires revealed that the mean age of participants was 26 years (SD = 7.2 years). The main reason for abortion was financial problems. With regard to marital status, 91.3% of the participants were married. Also, considering their job, 74.2% of the respondents were housewives, while 15.5% were employed in office jobs. Further, in 55.3% of the cases, abortion had been carried out as a result of the husband’s encouragement. The most common method of abortion was prescribing chemical medications, while the least popular method was intrauterine manipulations (with only 197 women reporting this abortion method). Moreover, 114 participants reported that they had accomplished curettage in a specialist physician’s office without anesthesia. The short-term complications of abortion included abdominal pain after abortion and incomplete abortion. On the other hand, long-term complications entailed visceral injury (1%), complications in the next pregnancy, bleeding in early pregnancy (10.7%), preterm delivery (7.9%), and ectopic pregnancy (7.4%). Conclusions: Scientific and religious education through appropriate procedures along with preventing unwanted pregnancy is a decisive factor in abortion

Prediction of Poisson’s ratio of worsted woven fabrics considering fabric extension in various directions

The paper aims to analyse the Poisson’s ratio of woven fabrics in terms of fabric tensile behavior in different directions. In this research, measurement of the Poisson’s ratio of a series of worsted woven fabrics has been carried out through uniaxial extension of the fabrics on the tensile testing machine and tracing the dimensional changes of them during the load application. By the use of the Matlab curve fitting toolbox, the best equation for representing the relationship between the Poisson’s ratio and the tensile load exerted to the fabric is derived. The mentioned function can be utilized for the prediction of the Poisson’s ratio at various levels of load. Due to the non-isotropic behaviour of the woven fabrics, the differences of the Poisson’s ratio obtained in the two main fabric directions (warp and weft) are investigated. Finally, the influence of weave structure and weft density on the Poisson’s ratio of the fabrics is studied. Analysis of the results reveals that the value of the Poisson’s ratio in terms of tensile load follows a similar trend for all the fabrics in both warp and weft directions. The mentioned trend is fitted reliably by a trigonometric function with the correlation factor (R2) of more than 92%. The result of investigating the Poisson’s ratio in two perpendicular directions is found in agreement with the structural changes of the fabric in different directions. Statistical analysis of results confirms that the effect of weave structure and weft density on the Poisson’s ratio is significant at the 95% confidence level.

Soil erosion prediction based on land cover dynamics at the Semenyih watershed in Malaysia using LTM and USLE models

This study attempts to identify and forecast future land cover (LC) by using the Land Transformation Model (LTM), which considers pixel changes in the past and makes predictions using influential spatial features. LTM applies the Artificial Neural Networks algorithm) in conducting the analysis. In line with these objectives, two satellite images (Spot 5 acquired in 2004 and 2010) were classified using the Maximum Likelihood method for the change detection analysis. Consequently, LC maps from 2004 to 2010 with six classes (forest, agriculture, oil palm cultivations, open area, urban, and water bodies) were generated from the test area. A prediction was made on the actual soil erosion and the soil erosion rate using the Universal Soil Loss Equation (USLE) combined with remote sensing and GIS in the Semenyih watershed for 2004 and 2010 and projected to 2016. Actual and potential soil erosion maps from 2004 to 2010 and projected to 2016 were eventually generated. The results of the LC change detections indicated that three major changes were predicted from 2004 to 2016 (a period of 12 years): (1) forest cover and open area significantly decreased at rates of almost 30 and 8 km2, respectively; (2) cultivated land and oil palm have shown an increment in sizes at rates of 25.02 and 5.77 km2, respectively; and, (3) settlement and Urbanization has intensified also by almost 5 km2. Soil erosion risk analysis results also showed that the Semenyih basin exhibited an average annual soil erosion between 143.35 ton ha−1 year−1 in 2004 and 151 in 2010, followed by the expected 162.24 ton ha−1 year−1. These results indicated that Semenyih is prone to water erosion by 2016. The wide range of erosion classes were estimated at a very low level (0–1 t/ha/year) and mainly located on steep lands and forest areas. This study has shown that using both LTM and USLE in combination with remote sensing and GIS is a suitable method for forecasting LC and accurately measuring the amount of soil losses in the future

Knowledge-based in silico models and dataset for the comparative evaluation of mammography AI for a range of breast characteristics, lesion conspicuities and doses

To generate evidence regarding the safety and efficacy of artificial intelligence (AI) enabled medical devices, AI models need to be evaluated on a diverse population of patient cases, some of which may not be readily available. We propose an evaluation approach for testing medical imaging AI models that relies on in silico imaging pipelines in which stochastic digital models of human anatomy (in object space) with and without pathology are imaged using a digital replica imaging acquisition system to generate realistic synthetic image datasets. Here, we release M-SYNTH, a dataset of cohorts with four breast fibroglandular density distributions imaged at different exposure levels using Monte Carlo x-ray simulations with the publicly available Virtual Imaging Clinical Trial for Regulatory Evaluation (VICTRE) toolkit. We utilize the synthetic dataset to analyze AI model performance and find that model performance decreases with increasing breast density and increases with higher mass density, as expected. As exposure levels decrease, AI model performance drops with the highest performance achieved at exposure levels lower than the nominal recommended dose for the breast type.Comment: NeurIPS 2023 Datasets and Benchmarks Trac

Comparing the adverse outcomes of contraception failure between IUD and withdrawal methods

Background: Objective of current study was to compare the adverse outcomes of pregnancy after failure of IUD (Intrauterine device) with the withdrawal method of contraception in order to predict and prevent such outcomes.Methods: In a retrospective cohort study, the adverse outcomes of 224 pregnancies (2 groups, 112 women each) were assessed following failure of the IUD or withdrawal methods of contraception (coitus interruptus). Data were analyzed and P values ≤0.05 were considered statistically significant.Results: Rates of spontaneous and induced abortion, ectopic pregnancy, and vaginal bleeding during second half of pregnancy were more common in the removed IUD group compared to the withdrawal method, differences however not significant. No fetal abnormality was observed in IUD group. Preterm birth (p= 0.045), preterm premature rupture of membrane (p= 0.01), and vaginal bleeding during pregnancy (p= 0.01), were more prevalent in the IUD group (retained and removed) compared to those using the withdrawal method.Conclusions: Considering the adverse outcomes, we knew women with pregnancy after failure of IUD were at an increased risk for such outcomes, compared to those using the withdrawal method; however the results of this research showed these adverse effects are not significant when pregnancy with IUD is detected earlier and IUD is removed during the early stage(s) of pregnancy

In vitro activity of some essential oils against Penicillium digitatum

Natural plant essential oils (EOs) can be used instead of synthetic fungicides because of human health concerns and environmental protection. In this study, the in vitro activity of some plants EOs against Penicillium digitatum, the cause of citrus green mold was evaluated during 8 days of incubation at 25°C. The EOs extracted from sweet orange (Citrus sinensis), lemon (Citrus limon), lime (Citrus aurantifolia), and sour orange (Citrus aurantium) fruit peel (500, 1000 and 2000 µl l-1 concentrations), cinnamon (Cinnamomum cassia) bark and summer savory (Satureja hortensis) aerial parts (400, 500 and 600 µl l-1 concentrations) were used on Penicillium digitatum mycelium. None of the EOs extracted from tested citrus in this study could inhibit mycelial growth completely even at concentration of 2000 µl l-1. The best results were obtained with cinnamon and summer savory EOs at concentration of 500 and 600 µl l-1. So, based on the results, cinnamon and summer savory EOs can be ideal candidates to replace the synthetic fungicides to control postharvest green mold of citrus fruit. GC-MS analysis showed that the most abundant of all constituents in EO extracts were carvacrol and γ-terpinene in summer savory and (E)-cinnamaldehyde in cinnamon

Influence of arbuscular mycorrhiza fungi, rice-husk-drived biochar and compost on dry matter yield, nutrients uptake and secondary metabolites responses of Iranian borage Echium amoenum Fisch & C. A. Mey

In einem Gewächshausversuch wurde der Einfluss von Bio-Düngern wie vesikulär-arbuskulärer Mykorrhiza, Biochar aus Reisspreu und Biokompost auf Ertrag, Nährstoffaufnahme und sekundäre Inhaltstoffe der Medizinalpflanze Echium amoneum; Fisch & C. A. Mey (iranisches Gurkenkraut) geprüft. Die Varianten waren komplett randomisiert. Alle Behandlungen zeigten signifikante Effekte auf Trockenmasse, Nährstoffaufnahme und Gehalte an Chlorophyll, Carotinoiden, Prolin, Anthocyanen, Flavonoiden, Schleimstoffen und Kohlenhydraten.This study was carried out to investigate the effect of bio-fertilizers including mycorrhiza (MY), rice husk compost (RHC), and biochar (RHB) on dry matter yield, nutrients uptake and some secondary metabolites of the medicinal plant Echium amoenum Fisch & C. A. Mey. The experiment was conducted in a completely randomized design and executed with six treatments and six replications. Treatments comprised of T1: control, T2: MY, T3: RHC, T4: RHB, T5: RHC+MY and T6: RHB+MY. The following parameters were studied: leaf dry weight, macro and micro nutrient uptake, chlorophyll a, chlorophyll b, carotenoids, proline, anthocyanin, flavonoid, mucilage and carbohydrate content. The results show that application of RHC, RHB and MY individually or in combination significantly affected the studied parameters in comparison with the control treatment. In all cases, combined appli­cation of bio-fertilizers together with mycorrhiza application (T5 and T6) had a more positive impact on the studied parameters compared to the application of each treatment alone

The effect of arbuscular mycorrhiza, rice husk compost and biochar on Iranian borage Echium amoenum Fisch & C. A. Mey and post-harvesting soil properties

In einem Gewächshausversuch wurde der Einfluss von Bio-Düngern, wie vesikulär-arbuskulärer Mykorrhiza, Compost und Biochar aus Azolla-Algen auf Ertrag, Ertragsstruktur sowie die Aufnahme an Haupt- und Spurenelementen von iranischem Gurkenkraut geprüft. Gegenstand der Untersuchung war auch der Nährstoffgehalt der Böden nach der Ernte, sowie deren biologische Aktivität. Alle geprüften Behandlungen zeigten im Vergleich zu den Kontrollen signifikante Effekte auf Ertrag und Nährstoffaufnahme. Höhere Bodenatmung und eine höhere mikrobielle Biomasse indizieren eine Steigerung der Fruchtbarkeit der Böden durch die Behandlungen. DOI: 10.5073/JfK.2019.01.02, https://doi.org/10.5073/JfK.2019.01.02This study was conducted to investigate the effect of rice husk compost (RHC), rice husk biochar (RHB) and mycorrhization (MY) on some properties of Iranian Echium amoenum Fisch & C. A. Mey and also on some selected post-harvesting soil properties. A completely randomized design experiment was conducted with six treatments and six replications. Treatments comprised T1: control, T2: MY, T3: RHC, T4: RHB, T5: RHC + MY and T6: RHB + MY. Studied parameters included; shoot and root fresh weights, root and leaf length, shrub height, leaf number, shoot and root NPK content, shoot and root Fe, Zn, Cu and Mn concentration, root colonization percentage, soil NPK status, soil micronutrients concentrations, soil respiration and microbial biomass. Results revealed that application of RHC, RHB and MY individually or in combination with other treatments significantly affected studied parameters. In all cases except for root colonization, combined application (T5 and T6) had more satisfied impacts compared with a single application of treatments. DOI: 10.5073/JfK.2019.01.02, https://doi.org/10.5073/JfK.2019.01.0

Impacts of PGPR, compost and biochar of Azolla on dry matter yield, nutrient uptake, physiological parameters and essential oil of Rosmarinus officinalis L.

In einem Gewächshausversuch wurde der Einfluss von Bio-Düngern wie PGPR, Compost und Biochar aus Azolla-Algen auf Ertrag, Nährstoffaufnahme und diverse Inhaltstoffe der Gewürzpflanze Rosmarin geprüft. Alle Behandlungen zeigten im Vergleich zu den Kontrollen sig­nifikante Effekte auf Ertrag, Nährstoffaufnahme und Gehalte an Chlorophyll, Carotinoiden, Flavonoiden, Kohlenhydraten, Prolin und essentielle Ölen. DOI: 10.5073/JfK.2019.01.01, https://doi.org/10.5073/JfK.2019.01.01Rosemary is one of the most important medicinal plants. In order to study the effect of plant growth promoting rhizobacteria (PGPR), Azolla compost and Azolla biochar on dry matter, nutrient uptake, physiological parameters and essential oil of rosemary, a greenhouse experiment was conducted in a completely randomized design with 6 replications. Treatments consisted of T1 (control), T2 (1% (1 g 100 g-1 dry soil) Azolla compost), T3 (1% Azolla biochar), T4 (PGPR (P. fluorescens)), T5 (1% compost + PGPR) and T6 (1% biochar + PGPR). Results indicated a significant enhancement of dry matter, nutrient uptake, photosynthetic pigments, carbohydrate, flavonoid and essential oil contents of rosemary influenced by organic fertilizers compared to control, particularly with co-appli­cation of PGPR + compost or biochar. Proline content decreased in all treatments in comparison with control. Results indicated positive impacts of PGPR, compost and boichar of Azolla on rosemary production by increasing nutrient uptake and protecting chlorophyll from degradation and enhancing its content in leaves. DOI: 10.5073/JfK.2019.01.01, https://doi.org/10.5073/JfK.2019.01.0