ANN modeling is used here to predict missing monthly precipitation data in one station of the eight weather stations network in Sulaimani Governorate. Eight models were developed, one for each station as for prediction. The accuracy of prediction obtain is excellent with correlation coefficients between the predicted and the measured values of monthly precipitation ranged from (90% to 97.2%). The eight ANN models are found after many trials for each station and those with the highest correlation coefficient were selected. All the ANN models are found to have a hyperbolic tangent and identity activation functions for the hidden and output layers respectively, with learning rate of (0.4) and momentum term of (0.9), but with different data set sub-division into training, testing and holdout data sub-sets, and different number of hidden nodes in the hidden layer. It is found that it is not necessary that the nearest station to the station under prediction has the highest effect; this may be attributed to the high differences in elevation between the stations. It can also found that the variance is not necessary has effect on the correlation coefficient obtained.
تم استخدام خرائط ضبط الجودة الإحصائية لتقييم جودة الخدمة التعليمية في جامعة الباحة، ويهدف هذا البحث إلى استخدام خرائط ضبط الجودة الإحصائية لقياس مستوى الجودة وفجوة الجودة بين توقعات الطلبة وإدراكاتهم لمستوى الخدمة الذي تقدمه جامعة الباحة. حيث تم اختيار عينة من 200 طالب وطالبة عشوائيا باستخدام العشوائية العنقودية من 4 كليات خلال الفترة 01 – 30/2015م، وجمعت البيانات من خلال استبيان جودة الخدمة الذي يقيس ت
... Show MoreA faunistic review of the genus Chaitophorus Koch, 1854, including four species in Iraq is given; the distribution data of each species and their hosts have been recorded. In this investigation the poplar leaf aphid Ch. populialbae (Boyer de Fonscolombe, 1841) is recorded here for the first time in Iraq on popular trees Populus euphratica Oliv. during the period from November 2016 to April 2017 in Baghdad province.
A brief description for apterous viviparous female of this species is given; and a key to the species of the genus Chaitophorus is constricted.
A new copolymer (MFA) was prepared from condensation of melamine (M) with p- methyl – anisole (A) in the presence of condensation agent like 37% (w/v) of formaldehyde. The new copolymer was characterized by elemental, IR and HNMR spectra. The chelating ion-exchange property of this polymer was studied for methylene blue dye in aqueous solution in 100-200ppm concentrations. The adsorption study was carried out over a wide range of pH, shaking time and in media of various kinetic parameters models. Thermal parameters like enthalpy, entropy and Gibbs free energy of adsorption process of methylene blue on surface of MFA resin were determined on the basis of kinetic parameters at different temperatures. To describe the equilibrium of adsorp
... Show MoreThe purpose of my thesis is to synthesis two new bidentate ligands which were used to prepare series of metal complexes by reacting the ligands with (M+2 = Mn, Co, Ni, Cu, Cd and Hg) Succinyl chloride was used as starting material to synthesis two bidentate ligands (L1) and (L2) by reaction it with 4-chloroaniline (L1) and (4-aminoacetophenone) (L2) in dichloromethane as a solvent, that are: (L1) = N1,N4-bis (4-chloro phenyl ) succinamide (L2) =N1,N4-bis(4-acetylphenyl)succinamide The new ligands were characterize by using spectroscopic study (Fourier-transform infrared spectroscopy (FT-IR), electronic spectra ( UV-Vis) ,nuclear magnetic resonance(1H,13C-NMR), Mass spectra
... Show MoreThis research deals with the financial reporting for non-current assets impairment from the viewpoint of international accounting standards, particularly IAS 36 "Impairment of non-current assets." The research problems focus on the presence of internal and external indicators on impairment of non-current assets in many of companies listed in Iraqi stock exchange. So it is required to apply IAS 36 to reporting for the impairment loss of assets since this impairment impact certain financial indicators. These indicators help users in their decision-making and forecasting future financial situation and the ability of the company to achieve future profits or maintain current profits. The research aims to shedding lig
... Show MoreSoftware-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne
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