Abstract: Many speaker language detection systems depend on deep learning (DL) approaches, and utilize long recorded audio periods to achieve satisfactory accuracy. This study aims to extract features from short recording audio files that are convenient in order to detect the spoken languages under test successfully. This detection process is based on audio files of (1 or 2) seconds whereas most of the previous languages Classification systems were based on much longer time frames (from 3 to 10 seconds). This research defined and implemented many low-level features using Mel Frequency Cepstral Coefficients (MFCCs), the dataset compiled by the researcher containing speech files in three languages (Arabic, English. Kurdish), which is called M2L_dataset is the source of data used in this paper.A Bidirectional Long Short-Term Memory (BiLSTM) algorithm applied in this paper for detection speaker language and the result was perfect, binary language detection had a test accuracy of 100%, and three languages detection had a test accuracy of 99.19%.

Abstract:           In this paper, the analytical solution to the problem of heat transfer and fluid flow was obtained by using the quadruple Laplace transform method. Temperature distribution and fluid flow distribution were shown, temperature and fluid flow increase when the value of z increases, as well as the effect of the radiation parameter  shown, it was concluded that the temperature increase with the increase in the value of the radiation coefficient . Matlab was used to plot the results.

Abstract: Abstract—The graphs which are used in this paper are simple, finite and undirected. The first and second Zagreb indices for every non-adjacent vertices (also called first and second Zagreb coindices) are dependent only on the non-adjacent vertices degrees which interspersed the operations of addition and multiplication, respectively, for the degrees of non-adjacent vertices. The number of the edges incident on vertex v in a graph G is called the degree of a vertex v and the two vertices u and v are non-adjacent if it’s no common edge between them. In this paper, we found the first and second Zagreb coindices of chains of even cycles and also, gave some examples.

Abstract: Block cipher algorithms are a very important issue in the field of information security. Their simple structure and software-based encryption allow users to implement them in several applications such as: data security and cloud computing. In this paper, we reviewed 8 block ciphers that had been presented in the recently five years and were used in different applications.  The 8 block ciphers are: DES, 3DES, Blowfish, Twofish, PRISENT, KLEIN, IDEA and AES. All of them are symmetric block ciphers with different designs. The comparative results showed that the block ciphers can still be used in different applications and fields. They showed that many modifications had been presented in which, chaotic maps had been implemented in key generation to enhance the robustness of the block ciphers and its randomness. The comparative results also showed that the AES is one of the block ciphers that is still unbroken algorithm and still modified to suit other new applications. Since less robust ciphers have continuous modification and enhancement in order to be more robust against some of probable attacks, the length of the key and its complexity and the structure of the ciphers are essential directions for improving block ciphers.

Abstract:   Voice is a behavioral biometric that may reveal a person's age, gender, ethnicity, and emotional state. Speaker recognition is the method of identifying individuals through their sounds. Despite the fact that over the last eight decades, academics have already been focusing on speaker identification, technological advancements like the Internet of Things (IoT), smart homes, voice assistants, smart gadgets and humanoids have made their use popular in modern society. This study offers a thorough analysis of the speaker identification literature. It looks at recent developments as well as problems in this area of study. This study looks into feature extraction, classifiers, and the structure of the speaker recognition system. Also covered is how speaker recognition is used in apps. The objective is to increase researchers' understanding of speaker identification by machine learning since recent research has shown that it is easy to deceive machine learning into producing an incorrect prediction.

Abstract: Real-time systems play a major role in our today's life. They are used in essential control systems that rely on timely response and determined outcomes to work. The main real-time scheduling algorithms for both soft and hard real-time system is presented in this paper, both in processors uniprocessor and multiprocessor schemes. The effectiveness of scheduling is derived from various factors, including hardware configuration, real-time application type, and real-time problem complexity. This review presents a characterization of scheduling techniques to help the researcher to get enough knowledge in real-time systems with adequate scheduling schemes to reach their timeliness characteristic. In this paper, we aim to investigate the scheduling attributes and scope of research in real-time computing, and classify real-time system in two categories: algorithms for multiprocessor scheduling and algorithms for uniprocessor scheduling. Furthermore, gives special attention to characteristic and their task, that is one of the following original contributions to real-time scheduling algorithms.

Abstract:                 People all over the world have experienced severe panic as a result of the novel coronavirus (COVID-19). To secure their future, it is crucial to undertake thorough evaluations in their psychological, physical, and social domains, comprehend the potential outcomes of patients recovering from it, and ascertain whether they have any other harmful diseases. This possible outcome for people recovered from Covid 19 was predicted by collecting data from people who had previously been infected with this virus to determine the effects they had, using intelligent techniques. The GSO algorithm was used for feature selection, and for hyper-parameter tuning for the Random Forest (RF) algorithm used in the prediction process in order to make predictions to identify the effects that may accrue on recoveries persons. This model was evaluated using different metrics after performing multiple processing operations on the data and using the GSO algorithm to perform the feature selection process in order to obtain the important features. Good results were obtained for each expected effect, as the highest AUC was obtained when predicting the impact of the gastrointestinal tract of recovered persons, which is 0.91. This will then reveal the effects that Covid-19 has had on people after they have recovered. This will assist in anticipating possible results to provide counseling and psychological support, as well as some recommended guidelines for healing patients and the community to return to a normal life.

Abstract: This research studies the spatial distribution quality of spatial interpolation methods. The research aims first to obtain unbiased estimator parameters based on regionalized variables in the study field. We used kriging techniques (called Local spatial interpolation) to rely on the variogram function with a fuzzy inference system, where fuzzy kriging is an extension of ordinary kriging. The second objective of this work is to estimate parameters of covariance models based on real data of soil chemicals, the data adopted in this research is taken from (100) real data for each soil chemical (Mg, Cl, and No3). These data are from Mosul Quadrangle in Mosul city in Iraq. After applying kriging techniques and a fuzzy inference system, we show the minimization of the estimation variance to choose the sentimental under uncertainty. We get the Smallest standard cross-validation of errors. Covariance models are described by exponential, and spherical model. With the best fitting models by the constraint of weights we note that the performance of the interpolation method is better by compared to the fuzzy system. In conclusion, the improvement does not rely on the statistical methods, but rather higher quality and large data of soil variables should be used to improve the prediction process. All programming computations are carried out in Matlab Language.

Abstract: In this paper, we study a reducible method which is called linearization(Linear-transform) for some non-linear stochastic differential equations (SDEs) to linear by using the Ito-integrated formula. And then finding their analytic solution, we compare the obtained solution for the nonlinear SDEs with the approximate solution by using numerical (Euler -Maruyama and Milstein) Methods.

Abstract:  The purpose of the present article  is to study and introduce the family of  holomorphic univalent functions defined on the open unit disk incluing the linear operators reduced by using the convolution concept between two familiar operators introduced by many authors and also studied in various families generalized by starlike and convex functions. Also, many mathematicians considered these families, our study deals with Bord distribution series, and we obtained many interesting geometric properties like the coefficient bounds of functions belonging to our family by proving the main result in characterization   theorem, we obtained also the bounds of the derivative of the operators   by proving the distortion theorem ,the extreme points also take into consideration and found them, the radii convexity and starlikeness are pointed out of functions belong to this family .

Abstract: In this paper, we study the extended graph theory in the sum group via Zpnq  which is   Zpnq  by two distinct orders, the sum is greatest than the order of the group Zpnq where p,q are prime numbers. We have some results that the group sum graph of Zpnq  are connected, cyclic, etc., if they satisfy some properties of the graph theory and compute all the degrees of graphs. Furthermore, we shall calculate the famous topological indices via generalized it.

Abstract: The software development life cycle includes software testing as a critical step. Oracle testing is necessary to determine if a particular test case detects an error because the purpose of testing is to ensure that the application adheres to its specifications. This test leads to the consumption of time and cost and may lead to errors in which the tester falls. This research aims to present a proposed system based on the automation of the Oracle test using intelligent techniques. The model was trained using the random forest algorithm and using the convolutional neural network. This proposed system is considered one of the box techniques. Test blacks that depend on the output of the system being tested.

Abstract: Restricted detour distance between two vertices    and of a graph  is the length of a longest u- v path  for the induced condition (V (P))=P. The restricted detour polynomial depends on restricted detour distance and is denoted by D*(G,x) and defined by D*(G,x) = ∑{u,v}xD*(u,v) where the summation is taken over all unordered pairs (u,v) of distinct vertices of u and v of V(G). In this paper, we investigate the restricted detour polynomial of the straight chain of wheel graphs φ(WkB) and compute the restricted detour index of φ(WkB).

Abstract: In this paper, we derive a new parameter µk-1 for the three-term CG (N3T) algorithm for solving unconstrained optimization problems. As demonstrated by its calculations and proof, the parameter µk-1 worth is determined by T , and the study mentions four different types of T . The search directions of this algorithm are always sufficiently descent when using strong Wolfe line search (SWC). Under reasonable assumptions, the proposed algorithm achieves global convergence. The numerical comparison demonstrates that our proposed method works well for solving unconstrained optimization problems.

Abstract: If for any maximal right ideal P of B and a ∈ N(B) ,aB/ aP is almost N-injective, then a ring B is said to be right generalized almost N-injective. In this article, we present some significant findings that are known for right almost N-injective rings and demonstrate that they hold for right generalized almost N-injective rings. At the same time, we study the case in which every S.S.Right B-module is generalized almost N-injective.