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MORPHOMETRIC FEATURES OF THE BEETLE ACINOPUS (ACINOPUS) LAEVIGATUS MENETRIES, 1832 (COLEOPTERA, CARABIDAE) IN THE MOUNTAIN ECOSYSTEMS OF UZBEKISTAN
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The morphometric parameters of Acinopus (Acinopus) laevigatus Ménétriés, 1832 (Coleoptera, Carabidae) were studied and their altitudinal variability was assessed. The length of head is the most variable, and the smallest value of the coefficient of variation is observed for the width of elytra. The length of body parts (head, pronotum, elytra) were more variable compared to their width. The correlation relationship between the morphometric parameters of different parts of the body was analyzed. A high correlation was found between the elytra length (EL) and the total body length (BL) (r=0.93), and the lowest correlation was found between the elytra width (EW) and the pronotum length (PL) (r=0.57). According to all measurement indicators, high-mountain representatives of beetles were inferior to middle-mountain individuals, and the variation in traits was also less. Only the width of the elytra turned out to be more variable in individuals of the highlands. Statistical analysis showed a rather high reliability of the influence of altitudinal belts on the morphometric parameters of beetles for all studied parameters. However, changes in body proportions in different altitudinal zones were not significant, except for the EW/BL index.

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Publication Date
Sat Apr 15 2023
Journal Name
Journal Of Robotics
A New Proposed Hybrid Learning Approach with Features for Extraction of Image Classification
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Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

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Publication Date
Sun Mar 12 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Effect of Lallemantia royleana Seeds Extract in Liver Functions Enzymes Levels and in some Mice Activity Features Treated with Rifadin drug
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    This study was aimed to investigate the role of crud alcoholic extract of Lallemantia royleana seeds in reducing the hepatotoxicity and side effect of rifadin drug in liver.                      The animals (40 mice) were divided into four groups, the first group was treated with normal saline (0.9%) for 28 days as a control and the second group was treated with rifadin (1.5 mg/kg/day) for 28 days and third group was treated with acoholic extract of Lallemantia royleana seeds (1% w/v) for 28 days, while the forth group was treated with alcoholic extract of seeds alone for 5 days and with alcoholic extract and rifadin for 28 days, so the total period of this group is 33

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Publication Date
Wed Apr 05 2023
Journal Name
International Journal Of Interactive Mobile Technologies (ijim)
A Partial Face Encryption in Real World Experiences Based on Features Extraction from Edge Detection
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User confidentiality protection is concerning a topic in control and monitoring spaces. In image, user's faces security in concerning with compound information, abused situations, participation on global transmission media and real-world experiences are extremely significant. For minifying the counting needs for vast size of image info and for minifying the size of time needful for the image to be address computationally. consequently, partial encryption user-face is picked. This study focuses on a large technique that is designed to encrypt the user's face slightly. Primarily, dlib is utilizing for user-face detection. Susan is one of the top edge detectors with valuable localization characteristics marked edges, is used to extract

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Publication Date
Tue Jul 18 2023
Journal Name
Journal Of Current Researches On Social Sciences
A Study on Sociocultural Features among Turkish and Iraqi Women
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SM ADAI, BN RASHID, Journal of Current Researches on Social Sciences, 2023

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Publication Date
Tue Jan 01 2013
Journal Name
International Journal Of Advanced Research In Computer Science And Software Engineering
Boundary & Geometric Region Features Image Segmentation for Quadtree Partitioning Scheme
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In this paper, an efficient image segmentation scheme is proposed of boundary based & geometric region features as an alternative way of utilizing statistical base only. The test results vary according to partitioning control parameters values and image details or characteristics, with preserving the segmented image edges.

Publication Date
Fri Apr 02 2021
Journal Name
New Trends In Information And Communications Technology Applications: 4th International Conference, Ntict 2020, Baghdad, Iraq, June 15, 2020, Proceedings 4
Iris recognition using localized Zernike features with partial iris pattern
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Publication Date
Mon Aug 01 2022
Journal Name
Telkomnika (telecommunication Computing Electronics And Control)
Dorsal hand veins features extraction and recognition by correlation coefficient
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Publication Date
Thu Jun 01 2023
Journal Name
Journal Of Engineering
A Modified Vigenère Cipher based on Time and Biometrics features
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Biometrics is widely used with security systems nowadays; each biometric modality can be useful and has distinctive properties that provide uniqueness and ambiguity for security systems especially in communication and network technologies. This paper is about using biometric features of fingerprint, which is called (minutiae) to cipher a text message and ensure safe arrival of data at receiver end. The classical cryptosystems (Caesar, Vigenère, etc.) became obsolete methods for encryption because of the high-performance machines which focusing on repetition of the key in their attacks to break the cipher. Several Researchers of cryptography give efforts to modify and develop Vigenère cipher by enhancing its weaknesses.

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Publication Date
Fri May 17 2019
Journal Name
Lecture Notes In Networks And Systems
Features Selection for Intrusion Detection System Based on DNA Encoding
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Intrusion detection systems detect attacks inside computers and networks, where the detection of the attacks must be in fast time and high rate. Various methods proposed achieved high detection rate, this was done either by improving the algorithm or hybridizing with another algorithm. However, they are suffering from the time, especially after the improvement of the algorithm and dealing with large traffic data. On the other hand, past researches have been successfully applied to the DNA sequences detection approaches for intrusion detection system; the achieved detection rate results were very low, on other hand, the processing time was fast. Also, feature selection used to reduce the computation and complexity lead to speed up the system

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Publication Date
Sun Mar 04 2012
Journal Name
Baghdad Science Journal
Biochemical and Kinetic Studies on Alkaline Phosphatase and other Biochemical Features in Sera of Patients with type 2 Diabetes
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Background :Alkaline phosphatase (ALP) was a widely used marker for skeletal and hepatobiliary disorders, but its activity was also increased in atherosclerosis and peripheral vascular disease. Several study has showed that ALP activity was increased in the sera of diabetic patients. The current study was conducted to evaluate ALP activity in type 2 diabetic patients and optimum conditions for enzyme activity in their sera.Methods: This study was carried out at in AL-Yarmok hospital(diabetic center) between February /2009 and April /2009. Fifty two patients with type 2 diabetes have been enrolled. Besides BMI, WHR, serum fasting blood glucose, ALP, HbA1C,uric acid and lipid profile levels have been performed .The relationship bet

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