University of Tabriz

About: University of Tabriz is a education organization based out in Tabriz, Iran. It is known for research contribution in the topics: Population & Nanocomposite. The organization has 12141 authors who have published 20976 publications receiving 313982 citations.

Landslide detection using multi-scale image segmentation and different machine learning models in the higher Himalayas

Abstract: Landslides represent a severe hazard in many areas of the world. Accurate landslide maps are needed to document the occurrence and extent of landslides and to investigate their distribution, types, and the pattern of slope failures. Landslide maps are also crucial for determining landslide susceptibility and risk. Satellite data have been widely used for such investigations—next to data from airborne or unmanned aerial vehicle (UAV)-borne campaigns and Digital Elevation Models (DEMs). We have developed a methodology that incorporates object-based image analysis (OBIA) with three machine learning (ML) methods, namely, the multilayer perceptron neural network (MLP-NN) and random forest (RF), for landslide detection. We identified the optimal scale parameters (SP) and used them for multi-scale segmentation and further analysis. We evaluated the resulting objects using the object pureness index (OPI), object matching index (OMI), and object fitness index (OFI) measures. We then applied two different methods to optimize the landslide detection task: (a) an ensemble method of stacking that combines the different ML methods for improving the performance, and (b) Dempster–Shafer theory (DST), to combine the multi-scale segmentation and classification results. Through the combination of three ML methods and the multi-scale approach, the framework enhanced landslide detection when it was tested for detecting earthquake-triggered landslides in Rasuwa district, Nepal. PlanetScope optical satellite images and a DEM were used, along with the derived landslide conditioning factors. Different accuracy assessment measures were used to compare the results against a field-based landslide inventory. All ML methods yielded the highest overall accuracies ranging from 83.3% to 87.2% when using objects with the optimal SP compared to other SPs. However, applying DST to combine the multi-scale results of each ML method significantly increased the overall accuracies to almost 90%. Overall, the integration of OBIA with ML methods resulted in appropriate landslide detections, but using the optimal SP and ML method is crucial for success.

Phytochemical constituents, advanced extraction technologies and techno-functional properties of selected Mediterranean plants for use in meat products. A comprehensive review

Abstract: Background Antioxidants and antimicrobials are increasingly becoming important additives in meat industry to extent shelf life and increase acceptability. Oxidative changes and microbiological activities have negative effects on the sensory, stability, nutritional and acceptability properties of the meat products. Mediterranean plant extracts and essential oils (EOs) have been studied as potential natural antimicrobials and antioxidant activity added to meat and meat products, as well as medicinal and functional properties. In recent years, plant derivatives are fairly becoming important in minimal processed products because of the high phenolic content, what allows to enhance the color stability and decrease off-flavors. Scope and approach This review provides recent information of phytochemical components, advanced extraction technologies and phenolic composition of Mediterranean plant extracts and EOs, as well as their antioxidant, antimicrobial, health promotion and sensory properties as natural preservatives in meat and meat products. Key findings and conclusions: A high concentration of phenolic and flavonoid content was observed in microwave assisted extraction (MAE), followed by ultrasound assisted extraction (UAE), conventional solvent extraction, and CO2 extraction. Phenolic acids and terpenoids were usually among the major components of common Mediterranean plant extracts and essential oils, respectively. Rosemary, garlic, lavender, leek, olive leaf, onion, oregano, pepper, peppermint, sage and Satureja montana are most important aromatic Mediterranean plant species used in meat industry and have exhibited similar or better antimicrobial and antioxidant properties than chemical preservatives. Flavonoids have beneficial effects on human and have been linked with the prevention of atherosclerosis, hypertension, dementia, diabetes and thrombosis.