Identification of pathogens and locating their inocul¬um source (S) are the first strategies toward successful disease management program the pretransplating seedl¬ing damping - off problem on vegetable crops was found to be caused by Pythium aphanidermatum and Rhizocto¬nia solani. Both fungi were isolated from peat (moss) for the first time in Iraq. In addition, considerable num¬ber of pathogenic fungi was found as contaminants in soil samples from Alrashidiah vegetable covered farming station. Among the isolated fungi were: Pythium apha¬nidermatum, Rhizoctonia solani, Sclerotinia sclerotiorum, Fusarium oxysporum, Fusarium solani phialophora spp., Cephalisporium spp Rizopus stolonfier and Botrytis cine¬rea, in addition to several of other folair pathogens Econo¬mic important diseases such as vascular wilt, stem and root rots, blight and fruit rots were found to be caused by those fungi on tomato, cucumber, cucurbit, eggplant and pepper plants that were grown at Alrashidiah. The results suggest that chemical, physical and / or biological treatments should be urgently applied for profitable vegetable growing at this station.
This study employs wavelet transforms to address the issue of boundary effects. Additionally, it utilizes probit transform techniques, which are based on probit functions, to estimate the copula density function. This estimation is dependent on the empirical distribution function of the variables. The density is estimated within a transformed domain. Recent research indicates that the early implementations of this strategy may have been more efficient. Nevertheless, in this work, we implemented two novel methodologies utilizing probit transform and wavelet transform. We then proceeded to evaluate and contrast these methodologies using three specific criteria: root mean square error (RMSE), Akaike information criterion (AIC), and log
... Show MoreThe main purpose of this work is to introduce some types of fuzzy convergence sequences of operators defined on a standard fuzzy normed space (SFN-spaces) and investigate some properties and relationships between these concepts. Firstly, the definition of weak fuzzy convergence sequence in terms of fuzzy bounded linear functional is given. Then the notions of weakly and strongly fuzzy convergence sequences of operators are introduced and essential theorems related to these concepts are proved. In particular, if ( ) is a strongly fuzzy convergent sequence with a limit where linear operator from complete standard fuzzy normed space into a standard fuzzy normed space then belongs to the set of all fuzzy bounded linear operators
This work implements an Electroencephalogram (EEG) signal classifier. The implemented method uses Orthogonal Polynomials (OP) to convert the EEG signal samples to moments. A Sparse Filter (SF) reduces the number of converted moments to increase the classification accuracy. A Support Vector Machine (SVM) is used to classify the reduced moments between two classes. The proposed method’s performance is tested and compared with two methods by using two datasets. The datasets are divided into 80% for training and 20% for testing, with 5 -fold used for cross-validation. The results show that this method overcomes the accuracy of other methods. The proposed method’s best accuracy is 95.6% and 99.5%, respectively. Finally, from the results, it
... Show MoreThe fingerprints are the more utilized biometric feature for person identification and verification. The fingerprint is easy to understand compare to another existing biometric type such as voice, face. It is capable to create a very high recognition rate for human recognition. In this paper the geometric rotation transform is applied on fingerprint image to obtain a new level of features to represent the finger characteristics and to use for personal identification; the local features are used for their ability to reflect the statistical behavior of fingerprint variation at fingerprint image. The proposed fingerprint system contains three main stages, they are: (i) preprocessing, (ii) feature extraction, and (iii) matching. The preprocessi
... Show MoreThe aim of this study is to shed light on the importance of biofuels as an alternative to conventional energy, in addition to the importance of preserving agricultural crops, which are the main source of this fuel, to maintain food security, especially in developing countries. The increase in global oil prices, in addition to the fear of global warming, are among the main factors that draw the world’s attention to searching for alternative sources of traditional energy, which are sustainable on the one hand, and on the other hand reduce carbon emissions. Therefore, the volume of global investment in renewable energy in general, and in liquid biofuels and biomass in particular, has increased. Global fears emerged that the excessive
... Show MoreA variety of new phenolic Schiff bases derivatives have been synthesized starting from Terephthaladehyde compound, all proposed structures were supported by FTIR, 1H-NMR, 13C-NMR, Elemental analysis, some derivatives evaluated by Thermal analysis (TGA).
This research aims at studying the relation between fair value and the Financial Reports Quality to achieve a number of aims such as :-
1- Throw light on the problems of the measurement that depends on the historic cost as it paves the way towards the method of the fair value in the accounting measurement.
2-Give a general definition for fair value in the accounting via analyzing the theoretical aspects that relates the subject and the scientific bases on which the relating accounting treatment depend.
3- Exhibit the characteristics that could be added by the fair value to the accounting Information .
The study problem is summarized in that the e
... Show MoreIn this paper, a handwritten digit classification system is proposed based on the Discrete Wavelet Transform and Spike Neural Network. The system consists of three stages. The first stage is for preprocessing the data and the second stage is for feature extraction, which is based on Discrete Wavelet Transform (DWT). The third stage is for classification and is based on a Spiking Neural Network (SNN). To evaluate the system, two standard databases are used: the MADBase database and the MNIST database. The proposed system achieved a high classification accuracy rate with 99.1% for the MADBase database and 99.9% for the MNIST database