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

 The current paper studied the concept of right n-derivation satisfying certified conditions on semigroup ideals of near-rings and some related properties. Interesting results have been reached, the most prominent of which are the following: Let M be a 3-prime left near-ring and A_1,A_2,…,A_n are nonzero semigroup ideals of M, if d is a right n-derivation of M satisfies on of the following conditions,
d(u_1,u_2,…,(u_j,v_j ),…,u_n )=0 ∀ 〖 u〗_1 〖ϵA〗_1 ,u_2 〖ϵA〗_2,…,u_j,v_j ϵ A_j,…,〖u_n ϵA〗_u;
d((u_1,v_1 ),(u_2,v_2 ),…,(u_j,v_j ),…,(u_n,v_n ))=0 ∀u_1,v_1 〖ϵA〗_1,u_2,v_2 〖ϵA〗_2,…,u_j,v_j ϵ A_j,…,〖u_n,v_n ϵA〗_u ;
d((u_1,v_1 ),(u_2,v_2 ),…,(u_j,v_j ),…,(u_n,v_n ))=(u_

This research discusses the subject of emotional stimulation factors through the stages of product design interaction with the consumer and what they reflect in the formation of a self-consideration of the design in his emotional memory regarding the specific brand through the following question (What is the emotional stimulus in the design of certain products and its reflection on the consumer during the processes of receiving and using it?), The importance of the research comes in the connection of design elements with many sensory factors used and motivating to attract the consumer to the acquisition of a specific design and the demand for its experience, the study aims Detection and access to emotional stimulation in the design of th

Background: Obesity tends to appear in modern societies and constitutes a significant public health problem with an increased risk of cardiovascular diseases.

Objective: This study aims to determine the agreement between actual and perceived body image in the general population.

Methods: A descriptive cross-sectional study design was conducted with a sample size of 300. The data were collected from eight major populated areas of Northern district of Karachi Sindh with a period of six months (10^th January 2020 to 21^st June 2020). The Figure rating questionnaire scale (FRS) was applied to collect the demographic data and perception about body weight. Body mass index (BMI) used for ass

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

An overall mathematical model for copper pipe corrosion in flowing water was derived based on mass transfer fundamentals where we introduced the effects of boundary layer velocity, bulk flow velocity and the surface oxide protective film on the corrosion rate. A set of experiments were conducted in a straight 10mm diameter copper pipe, flow of water include six velocities of maximum value 7.33m/sec at 200C and 350C. The good agreement between the calculated and experimental corrosion rate values were achieved , the agreement reached 92% .

Finding a new source of resistance is important to reduce the use of synthetic pesticides, which can meet the global need of suppressing pollution. In this study, the resistance of eight eggplant cultivars to Aphis gossypii was evaluated. Results of the current study highlighted that the cultivar Long-Green has a very strong resistance after 14 days post infestation whereas Pearl-Round and White-Casper cultivars were susceptible. The rest of the tested cultivars (Green-oblong, Purple-panter, Paris, Ashbilia, and Barcelona) had mild resistance. Also, the study found significant differences between the infested and non-infested plants among the tested cultivars in the plant’s height, fresh-, and dry-weight. The susceptible cultivars

In 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