Mammals are under threat worldwide due to deforestation, hunting, and other human activities. In Iraq, a total of 93 species of wild mammals have been recorded including species with global conservation concern. Bamo Mountain is situated within the Zagros Mountains in northern Iraq which is a suitable habitat for wild mammals. Due to scarcity of the field survey efforts and cryptic behavior, monitoring of the wild mammals fauna in Zagros Mountain seems challenging. Therefore, we used a camera trap which seems to be an ideal way to determine species diversity of wild mammals in Bamo Mountain. Moreover, interviews with local villagers were performed. The mammalian diversity of Bamo Mountain is not fully explored but seemed threatened by local extinction due to poaching and wildlife trafficking, minefields, and annual fires.
In this study, a total of eight species of wild mammals were recorded for the first time in Bamo Mountain using camera trap method including the Persian leopard Panthera pardus saxicolor Pocock, 1927, and the Wild goat Capra aegagrus Erxleben, 1777, flagship and key species of conservation concern. As far as it is concerned, the major threats on the wild mammals were discussed and some important points were highlighted towards the establishment of the protected area in Bamo Mountain.
In information security, fingerprint verification is one of the most common recent approaches for verifying human identity through a distinctive pattern. The verification process works by comparing a pair of fingerprint templates and identifying the similarity/matching among them. Several research studies have utilized different techniques for the matching process such as fuzzy vault and image filtering approaches. Yet, these approaches are still suffering from the imprecise articulation of the biometrics’ interesting patterns. The emergence of deep learning architectures such as the Convolutional Neural Network (CNN) has been extensively used for image processing and object detection tasks and showed an outstanding performance compare
... Show MoreSemi-parametric models analysis is one of the most interesting subjects in recent studies due to give an efficient model estimation. The problem when the response variable has one of two values either 0 ( no response) or one – with response which is called the logistic regression model.
We compare two methods Bayesian and . Then the results were compared using MSe criteria.
A simulation had been used to study the empirical behavior for the Logistic model , with different sample sizes and variances. The results using represent that the Bayesian method is better than the at small samples sizes.
... Show MoreSoil water use and water storage vary by vegetative management practices, and these practices affect land productivity and hydrologic processes. This study investigated the effects of agroforestry buffers (AB), grass buffers (GB), and biofuel crops (BC), relative to row crops (RC) on soil water use for a claypan soil in northern Missouri, USA. The experiment located at the Greenley Memorial Research Center included RC, AB, GB, and BC established in 1991, 1997, 1997, and 2012, respectively. Soil water reflectometer sensors installed at 5‐, 10‐, 20‐, and 40‐cm depths monitored soil water from April to November in 2017 and 2018. Results showed significant differences in weekly volumetric water content (VWC) among treatments for all fou
... Show MoreThis research aims to removes dyes from waste water by adsorption using banana peels. The conduct experiment done by banana powder and banana gel to compare between them and find out which one is the most efficient in adsorption. Studying the effects different factors on adsorption material and calculate the best removal efficiency to get rid of the methylene blue dye (MB).
In this research, Artificial Neural Networks (ANNs) technique was applied in an attempt to predict the water levels and some of the water quality parameters at Tigris River in Wasit Government for five different sites. These predictions are useful in the planning, management, evaluation of the water resources in the area. Spatial data along a river system or area at different locations in a catchment area usually have missing measurements, hence an accurate prediction. model to fill these missing values is essential.
The selected sites for water quality data prediction were Sewera, Numania , Kut u/s, Kut d/s, Garaf observation sites. In these five sites models were built for prediction of the water level and water quality parameters.
Cover crops (CC) improve soil quality, including soil microbial enzymatic activities and soil chemical parameters. Scientific studies conducted in research centers have shown positive effects of CC on soil enzymatic activities; however, studies conducted in farmer fields are lacking in the literature. The objective of this study was to quantify CC effects on soil microbial enzymatic activities (β-glucosidase, β-glucosaminidase, fluorescein diacetate hydrolase, and dehydrogenase) under a corn (Zea mays L.)–soybean (Glycine max (L.) Merr.) rotation. The study was conducted in 2016 and 2018 in Chariton County, Missouri, where CC were first established in 2012. All tested soil enzyme levels were significantly different between 2016 and 2018
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