The utilization of artificial intelligence techniques has garnered significant interest in recent research due to their pivotal role in enhancing the quality of educational offerings. This study investigated the impact of employing artificial intelligence techniques on improving the quality of educational services, as perceived by students enrolled in the College of Pharmacy at the University of Baghdad. The study sample comprised 379 male and female students. A descriptive-analytical approach was used, with a questionnaire as the primary tool for data collection. The findings indicated that the application of artificial intelligence methods was highly effective, and the educational services provided to students were of exceptional

Background: The aim of this study was to evaluate the effect of thermo cycling and different pH of artificial saliva (neutral, acidic, basic) on impact and transverse strength of heat cure acrylic resin reinforced of with 5% silanated ZrO2 nano fillers. Materials and methods: 120 samples were prepared, 60 samples for impact strength test and another 60 samples for transverse strength test, for each test, samples were divided into two major groups (before and after thermo cycling), then each of these major groups were further subdivided into 3 subgroups according to the pH of prepared artificial saliva (neutral, acidic, basic). Charpy impact device was used for impact strength test and Flexural device was used for transverse strength test. R

In Automatic Speech Recognition (ASR) the non-linear data projection provided by a one hidden layer Multilayer Perceptron (MLP), trained to recognize phonemes, and has previous experiments to provide feature enhancement substantially increased ASR performance, especially in noise. Previous attempts to apply an analogous approach to speaker identification have not succeeded in improving performance, except by combining MLP processed features with other features. We present test results for the TIMIT database which show that the advantage of MLP preprocessing for open set speaker identification increases with the number of speakers used to train the MLP and that improved identification is obtained as this number increases beyond sixty.

In this paper, integrated quantum neural network (QNN), which is a class of feedforward

neural networks (FFNN’s), is performed through emerging quantum computing (QC) with artificial neural network(ANN) classifier. It is used in data classification technique, and here iris flower data is used as a classification signals. For this purpose independent component analysis (ICA) is used as a feature extraction technique after normalization of these signals, the architecture of (QNN’s) has inherently built in fuzzy, hidden units of these networks (QNN’s) to develop quantized representations of sample information provided by the training data set in various graded levels of certainty. Experimental results presented here show that

The objective of this work is to design and implement a cryptography system that enables the sender to send message through any channel (even if this channel is insecure) and the receiver to decrypt the received message without allowing any intruder to break the system and extracting the secret information. In this work, we implement an interaction between the feedforward neural network and the stream cipher, so the secret message will be encrypted by unsupervised neural network method in addition to the first encryption process which is performed by the stream cipher method. The security of any cipher system depends on the security of the related keys (that are used by the encryption and the decryption processes) and their corresponding le

In this paper, precision agriculture system is introduced based on Wireless Sensor Network (WSN). Soil moisture considered one of environment factors that effect on crop. The period of irrigation must be monitored. Neural network capable of learning the behavior of the agricultural soil in absence of mathematical model. This paper introduced modified type of neural network that is known as Spiking Neural Network (SNN). In this work, the precision agriculture system  is modeled, contains two SNNs which have been identified off-line based on logged data, one of these SNNs represents the monitor that located at sink where the period of irrigation is calculated and the other represents the soil. In addition, to reduce p

Adenosine deaminase (ADA; Ec: 3.5.4.4), 5´- Nucleotidase (5´– NT; Ec: 3.1.3.5), and AMP – amino hydrolase (AMP – deaminase AMPDA; Ec: 3.5.4.6) activities were measured in sera of ovarian cancer patients before surgery, and after chemotherapy. The results indicated that ADA specific activity increased significantly (P<0.05), while 5´-NT and AMPDA specific activity decreased significantly (P<0.05) in ovarian cancer patients before surgery in comparison with those of their corresponding control women and benign tumors groups. When the activities of these enzymes were measured after chemotherapy, a significant decrease (P<0.05) in ADA activity, and a significant increase (P<0.05) in 5´- NT and AMPDA activities w

The inhibition effect of crude juice of green and black olive on cancer cell line (RD) in vitro has been studied by depending on micro titration system . Eleven different concentration starting from (916-960) mg/ml of crude juice respectively ,for three periods of exposure(24-48-72)hours. The resulted showed that the inhibition effect dependent on type of olive fruit juice ,concentration of dose ,time of exposure and the high concentration of both type of olive juice increased the growth of cell line while other concentration caused decrease in different rates ,moreover the black juice was more effective than green and 48 hours' time exposure was the best for inhibition.

The estimation of the regular regression model requires several assumptions to be satisfied such as "linearity". One problem occurs by partitioning the regression curve into two (or more) parts and then joining them by threshold point(s). This situation is regarded as a linearity violation of regression. Therefore, the multiphase regression model is received increasing attention as an alternative approach which describes the changing of the behavior of the phenomenon through threshold point estimation. Maximum likelihood estimator "MLE" has been used in both model and threshold point estimations. However, MLE is not resistant against violations such as outliers' existence or in case of the heavy-tailed error distribution. The main goal of t

The purpose behind building the linear regression model is to describe the real linear relation between any explanatory variable in the model and the dependent one, on the basis of the fact that the dependent variable is a linear function of the explanatory variables and one can use it for prediction and control. This purpose does not cometrue without getting significant, stable and reasonable estimatros for the parameters of the model, specifically regression-coefficients. The researcher found that "RUF" the criterian that he had suggested accurate and sufficient to accomplish that purpose when multicollinearity exists provided that the adequate model that satisfies the standard assumpitions of the error-term can be assigned. It