Been Antkhav three isolates of soil classified as follows: Bacillus G3 consists of spores, G12, G27 led Pal NTG treatment to kill part of the cells of the three isolates varying degrees treatment also led to mutations urged resistance to streptomycin and rifampicin and double mutations

HM Al-Dabbas, RA Azeez, AE Ali, Iraqi Journal of Science, 2023

The experiment was conducted to evaluate and performance comparison for moldboard and disk plows in central of Iraq in 2011. Three factor were used in this study included Two types of plows included moldboard and disk plows which represented main plot , three forward speeds of the tillage was second factor included 1.85, 3.75 and 5.62 km / h which represented sup plot , and three levels of soil moisture was third factor included 21 , 18 and 14 % to determined data actual plow depth , Practical productivity, Volume of disturbed soil, Field efficiency , Slippage percentage in silt clay loam soil with depth 22 cm were studied in the experiment Split – split plot design under randomized complete block design with three replications using

In this study, performance characteristics such as power take off (PTO) power consumption, fuel consumption, fuel consumption for the unit field-unit product were determined at different working speeds with two different PTO applications (540 and 540E) in a single row disc type silage machine. In particular, the 540E PTO application greatly reduces fuel consumption for unit work. The best results in terms of hourly fuel consumption were achieved in 540E PTO application and V1 working speed. When the field - product fuel consumption is evaluated, the best results were obtained with the 540E PTO application at the V3 working speed. When an evaluation is made considering all the parameters, it is concluded that the 540E PTO application will p

Image recognition is one of the most important applications of information processing, in this paper; a comparison between 3-level techniques based image recognition has been achieved, using discrete wavelet (DWT) and stationary wavelet transforms (SWT), stationary-stationary-stationary (sss), stationary-stationary-wavelet (ssw), stationary-wavelet-stationary (sws), stationary-wavelet-wavelet (sww), wavelet-stationary- stationary (wss), wavelet-stationary-wavelet (wsw), wavelet-wavelet-stationary (wws) and wavelet-wavelet-wavelet (www). A comparison between these techniques has been implemented. according to the peak signal to noise ratio (PSNR), root mean square error (RMSE), compression ratio (CR) and the coding noise e (n) of each third

Over the past few years, ear biometrics has attracted a lot of attention. It is a trusted biometric for the identification and recognition of humans due to its consistent shape and rich texture variation. The ear presents an attractive solution since it is visible, ear images are easily captured, and the ear structure remains relatively stable over time.  In this paper, a comprehensive review of prior research was conducted to establish the efficacy of utilizing ear features for individual identification through the employment of both manually-crafted features and deep-learning approaches. The objective of this model is to present the accuracy rate of person identification systems based on either manually-crafted features such as D

The area of character recognition has received a considerable attention by researchers all over the world during the last three decades. However, this research explores best sets of feature extraction techniques and studies the accuracy of well-known classifiers for Arabic numeral using the Statistical styles in two methods and making comparison study between them. First method Linear Discriminant function that is yield results with accuracy as high as 90% of original grouped cases correctly classified. In the second method, we proposed algorithm, The results show the efficiency of the proposed algorithms, where it is found to achieve recognition accuracy of 92.9% and 91.4%. This is providing efficiency more than the first method.

Document analysis of images snapped by camera is a growing challenge. These photos are often poor-quality compound images, composed of various objects and text; this makes automatic analysis complicated. OCR is one of the image processing techniques which is used to perform automatic identification of texts. Existing image processing techniques need to manage many parameters in order to clearly recognize the text in such pictures. Segmentation is regarded one of these essential parameters. This paper discusses the accuracy of segmentation process and its effect over the recognition process. According to the proposed method, the images were firstly filtered using the wiener filter then the active contour algorithm could b

Emotion recognition has important applications in human-computer interaction. Various sources such as facial expressions and speech have been considered for interpreting human emotions. The aim of this paper is to develop an emotion recognition system from facial expressions and speech using a hybrid of machine-learning algorithms in order to enhance the overall performance of human computer communication. For facial emotion recognition, a deep convolutional neural network is used for feature extraction and classification, whereas for speech emotion recognition, the zero-crossing rate, mean, standard deviation and mel frequency cepstral coefficient features are extracted. The extracted features are then fed to a random forest classifier. In