Box-Wilson experimental design method was employed to optimized lead ions removal efficiency by bulk liquid membrane (BLM) method. The optimization procedure was primarily based on four impartial relevant parameters: pH of feed phase (4-6), pH of stripping phase (9-11), carrier concentration TBP (5-10) %, and initial metal concentration (60-120 ppm). maximum recovery efficiency of lead ions is 83.852% was virtually done following thirty one-of-a-kind experimental runs, as exact through 2⁴-Central Composite Design (CCD). The best values for the aforementioned four parameters, corresponding to the most restoration efficiency were: 5, 10, 7.5% (v/v), and 90 mg/l, respectively. The obtained experimental data had been

In aspect-based sentiment analysis ABSA, implicit aspects extraction is a fine-grained task aim for extracting the hidden aspect in the in-context meaning of the online reviews. Previous methods have shown that handcrafted rules interpolated in neural network architecture are a promising method for this task. In this work, we reduced the needs for the crafted rules that wastefully must be articulated for the new training domains or text data, instead proposing a new architecture relied on the multi-label neural learning. The key idea is to attain the semantic regularities of the explicit and implicit aspects using vectors of word embeddings and interpolate that as a front layer in the Bidirectional Long Short-Term Memory Bi-LSTM. First, we

The research aimed to statement, which impact that the development of Iraqi auditing standards in the fight against corruption and to fulfill the reform requirements by conducting a comparative study analysis with a framework proposal to amend the Iraqi Audit directory number statement (6) issued by the Accounting and Auditing Standards Board of the Republic of Iraq dated 08/24/2002 on audit planning and supervision on the basis of the latest versions of international auditing standards in this regard.

The researchers concluded that there is a need to update the standards (evidence) audit accredited in the Republic of Iraq in accordance with international auditing standards to meet the requirements of the report of the external a

Data-driven models perform poorly on part-of-speech tagging problems with the square Hmong language, a low-resource corpus. This paper designs a weight evaluation function to reduce the influence of unknown words. It proposes an improved harmony search algorithm utilizing the roulette and local evaluation strategies for handling the square Hmong part-of-speech tagging problem. The experiment shows that the average accuracy of the proposed model is 6%, 8% more than HMM and BiLSTM-CRF models, respectively. Meanwhile, the average F1 of the proposed model is also 6%, 3% more than HMM and BiLSTM-CRF models, respectively.

The search is contain compared among some order selection criteria  (FPE,AIC,SBC,H-Q) for the Model first order  Autoregressive when the White Noise is follow Normal distribution and some of non Gaussian distributions (Log normal, Exponential and Poisson distribution ) by using Simulation  

This study, establishes two stochastic monotonicity results concerning the run length of an upper one –sided Exponentially Weighted Moving Average (EWMA) control charts, based on the logarithm of the sample variance, for monitoring a process standard deviation, these properties cast interesting light on the control chart performance, and their extension to other one –sided EWMA control charts.

Offline handwritten signature is a type of behavioral biometric-based on an image. Its problem is the accuracy of the verification because once an individual signs, he/she seldom signs the same signature. This is referred to as intra-user variability. This research aims to improve the recognition accuracy of the offline signature. The proposed method is presented by using both signature length normalization and histogram orientation gradient (HOG) for the reason of accuracy improving. In terms of verification, a deep-learning technique using a convolution neural network (CNN) is exploited for building the reference model for a future prediction. Experiments are conducted by utilizing 4,000 genuine as well as 2,000 skilled forged signatu

Several attempts have been made to modify the quasi-Newton condition in order to obtain rapid convergence with complete properties (symmetric and positive definite) of the inverse of  Hessian matrix (second derivative of the objective function). There are many unconstrained optimization methods that do not generate positive definiteness of the inverse of Hessian matrix. One of those methods is the symmetric rank 1( H-version) update (SR1 update), where this update satisfies the quasi-Newton condition and the symmetric property of inverse of Hessian matrix, but does not preserve the positive definite property of the inverse of Hessian matrix where the initial inverse of Hessian matrix is positive definiteness. The positive definite prope

Certainly there is a negative impact on development due to corruption in its corruption forms It is administrative and financial as well as direct impact on all sectors Including the health sector, which has seen in Iraq a marked setback in performance and services , The research aims at the possibility of demonstrating the negative effects of financial and administrative corruption on health institutions and Inability to meet health needs The extent to which Regulatory institutions and institutions manage to reduce financial and administrative corruption and ways of dealing with it The phenomenon of financial and administrative corruption is the most serious phenomenon because of its impact on economic growth, which in turn impedes the

Speech recognition is a very important field that can be used in many applications such as controlling to protect area, banking, transaction over telephone network database access service, voice email, investigations, House controlling and management ... etc. Speech recognition systems can be used in two modes: to identify a particular person or to verify a person’s claimed identity. The family speaker recognition is a modern field in the speaker recognition. Many family speakers have similarity in the characteristics and hard to identify between them. Today, the scope of speech recognition is limited to speech collected from cooperative users in real world office environments and without adverse microphone or channel impairments.