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In this work, the utilization of waste paper in the preparation of cellulous-based composite is described, with latex as a binder. Paraffin wax and acrylic woven fibers were also used at various weight ratios to get the best mechanical and physical properties. The results were compared with the performance the Dixon, regularly used material in shoes manufacturing. The following tests were performed: compression resistance, density, water absorption, shrinkage, and moisture content. Manual method was employed in the preparation of test specimens in addition to laboratory forging machine for finishing of the specimens. Results of compression test (Modulus of elasticity, compressive strength, resistance to crushing) of the Specimens that contain pulp paper and reinforced with latex and acrylic fibers and low content of paraffin wax showed the highest resistance to compression, The increase of additives contents within the mix resulted in an increase in density. To mimic the real application conditions of the insole, the specimens were subjected to water absorption test by irrigation for 2 hours. The best specimen compositions for the water resistance test are those with high (5-10%) wax content due to the fact that the wax is a water repellent material. The shrinkage is another important parameter for the use of the composite in shoe industry. Result of shrinkage and humidity of all specimens show comparable results to commercially available and Dixon are also very close to the requirements of the specification of leather industry. However, in comparison with the available carton and dixon, our specimens contain from weight fraction (50g) waste pulp, (20g) latex, (4g) paraffin wax, (0.7g) acrylic fibers, proved comparable performance.

In this paper, we proposed new techniques to solve one of the important fields of the Combinatorial Optimization Problem, which is the problem of machine scheduling. The problem which wants to be solved in this paper is the total tardiness times and range of lateness. For bi-criteria we have (1//(∑Tj,RL)) while for bi-objective we have (1//(∑Tj+RL)). In order to solve the suggested two problems, some new exact and approximation methods are suggested which are produced good results. The results which are obtained from applying the newly proposed methods are compared with the exact method; like Complete Enumeration Method (CEM), then compared results of the heuristics with each other's to obtain the most efficient method.

The use of Deep Learning (DL) for identifying false or misleading information, known as fake news, is a growing area of research. Deep learning, a form of machine learning that utilizes algorithms to learn from large data sets, has shown promise in detecting fake news. The spread of fake news can cause significant harm to society economically, politically, and socially, and it has become increasingly important to find ways to detect and stop its spread. This paper examines current studies that use deep learning methods, such as Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs), as well as the multi-model approach, to detect fake news. It also looks at the use of word embedding models to convert text to vector representations and the datasets used for training models. Furthermore, the paper discusses the use of the attention mechanism in conjunction with deep learning to process sequential data.

A secure electronic learning platform has been created to enable teachers and students to log into their accounts to learn efficiently and safely at any place and time. This platform has been proposed due to the urgent need to develop the education system and move it from traditional to interactive e-learning. In this paper, an application implemented that access remotely using a web browser interface and saved on a server depends on a Zero-Knowledge Proof (ZKP) system with an RSA algorithm was employed to solve registration and login challenges and securely transfer passwords. Using adapted AES to encrypt each user's personal information, Exams, and save it in in encrypted form in the database. The simulated results in this paper indicate the existence of a secure e-learning system, where security was achieved by performing the registration and login process without sending the password in its explicit form over an insecure network such as the Internet, in addition to encrypting the necessary information to be stored in an incomprehensible manner in the database, in the case of presence of an attack on the database.

The utilize of the web has made humans and companies powerless to exterior assaults. Indeed, cyber problems essentially influence information frameworks with distinctive types of malicious attacks such as spyware, virus, social engineering, etc. The Internet e-mail service, in particular, has become one of the most dependable methods of communication among people, institutions, and companies. The development of digital signatures to e-mail services has raised the e-mail security, which led to replacing the standard mailing of registered letters. Unfortunately, the process of sending and receiving e-mails has created a negative impact means on security and privacy from cybercriminals by diffusing spam and malware. As a result, e-mail hosts are constantly under attack by malicious programs that are often attached to e-mails. In this paper, the simulation model and prototype of an email traffic monitor developed and tested in order to prove the ability of our proposed method for detecting new viruses. This paper states the success possibility of this new method based on the simulation results. The results of the analysis suggest that the Cyber Security Modeling Language (CySeMoL) model has a good performance of operating system vulnerability prediction. At last, some useful suggestions in the context of the CySeMoL model are presented.

Due to the rapid evaluation in the field of communications and multimedia and the increasing use of the Internet, multimedia data security has become very urgent. of the best alternative way to achieve multimedia data security is encryption, which prevents unauthorized entities from accessing confidential data. In recent years, the chaotic system of image encryption becomes an efficient way to encrypt images due to its high security. It has certain special properties like sensitivity to initial conditions, and control parameters, pseudorandom, ergodicity, and non-convergence, etc. chaotic dynamics systems became a promising alternative to traditional encryption algorithms. In this paper, This paper presents a new algorithm for the image encryption/decryption scheme depended on a novel six-dimensional hyper-chaotic system to achieve a high level of security, the chaotic sequence generated from system employ for permutation and diffusion the original image to create an encrypted image. The performance of the algorithm has been analyzed through analyzes statistical such as Histogram Analysis, Correlation Coefficient Analysis, Information Entropy Analysis, Key Space Analysis, Key Sensitivity Analysis, Number of Pixels Change Rate (NPCR), Unified Average Changing Intensity (UACI), Peak Signal to Noise Ratio, The experimental results show that the algorithm has good encryption performance, large keyspace equals to and the high sensitivity for small changes in secret key which makes the algorithm immune to Brute force attacks, and it can resist the statistical attacks, therefore, the presented encryption algorithm depends on a novel hyperchaotic system is more secure against the statistical and differential attacks.

The process of detect the text from the natural image is complex and difficult process because the variance by the devises that take the images and different the texts that found in images in the orientation, size and style. Given the importance the texts in images in the several of application of computer vision. In this paper dependent on the spatial natural images and on the spatial data set for the street sign that include the texts by the different size and different orientation. In this paper detected the texts in images by using robust method by using several algorithms, at the first stage making preprocessing for the image to blur the image and reduce the nose on it by Gaussian blur, second stage making processing that include canny edge detection to detect the edges and dilation, third stage applying connected component to filling all objects in image then applying stroke width transform(SWT) to detect the letter candidate and applying the system on the several images that include different types of texts.

With the tremendous development witnessed by the world in recent times, computer security significance expanded as insurance procedure of registering systems and authentication the user with scientific and technological developments are increasing every day. This assurance procedure is connected for touchy information such of electronic business, electronic learning, and electronic saving money exchange, online networking and more administrations over the web by utilizing login application to distinguish the character for doing this authentication. The problem by using some application login how to detected the user authentic and experimental data collection and separated the duplicated name that may be Confusion the system with speed detected and difficult attack. This paper solve this problem by used Cubic spline to easy represented name and easy detected by distance Euclidean equation, authentication techniques utilized as insurance process by securing name mix with Blum Blum Shub (BBS) algorithm that have randomly number. In this work, the application is founded on type name that the combine with (BBS) and represented by cubic spline, to detected user. The result of proposed work require randomly number to drawing the curve to detect and how much the different shape in cubic spline curve that can be detected. Assurance gives affirmation distinguished suitable security and all the more effortlessly least complex that developing popular in the online application that shows in result some portion of the paper

In this paper, the fire color feature is analysis and test on a set of color spaces (RGB, HSV, YCbCr, Lab, Yiq) to account the hue component and determination the best color space to represent the properties of fire and used in fire detection to increase accuracy and reduce the detection time and false alarms,four common types of fire (wood, cork, cloth, paper or cardboard ) were used to compare them with an image containing all the basic colors and analyze them and calculating Scale factor that depending on the histogram for hues value

The security of video applications in mobile devices has become recently an important field research. Dealing with video data, which is large compared to text and image and processing it in the mobile platform is a big challenge. Generally, the efficiency of any video encryption algorithm is concerned with two criteria, the computational time required to process video data, and the memory usage according to the resources on the smartphone. The secured system in 3G devices has become a matter of importance. This paper presents an implementation of full video encryption using Elliptic Curve Cryptography (ECC) on a mobile device. The operations on ECC include doubling and addition on the finite field as the backbone for an elliptic curve. Also, mapping representation is introduced to convert every byte of plain video into a point on EC. The paper proposed multi-keys instead of using one key as usual. Also, Chaotic Key Generator (CKG) is exploited for the randomness of the multi-keys. The proposed work focuses on increasing the security with multi-keys and to get acceptable time for encryption and decryption in a limited environment like mobile. The system is implemented using Android Studio with version (3.0) and using java language, it is implemented on Android version 7.0 (Nougat) and on mobile Galaxy S8.

Background: This paper addresses specific challenges in predictive modeling, namely transparency issues, susceptibility to data manipulation, and fairness concerns. To overcome these obstacles, the study introduces DeepRing, approach that combines Convolutional Neural Networks (CNNs) and blockchain technology. Objective: DeepRing aims to enhance prediction integrity, data security, and fairness, thereby improving the ethical considerations, reliability, and accountability of predictive models. Methods: involves iterative training of a CNN model on five diverse datasets, including CIFAR-10, Fashion-MNIST, MNIST, CIFAR-100, and a Hands dataset. The CNN architecture incorporates Conv2D layers, MaxPooling2D layers, and Dense layers. Training metrics such as accuracy and sparse categorical cross-entropy loss are monitored, with the Adam optimizer employed. While achieving high accuracy on Plam (0.5300), MNIST (0.9978) and Fashion MNIST (0.9673), DeepRing exhibits moderate performance on CIFAR-10 (0.9296) and lower accuracy on CIFAR-100 (0.5973). Results: demonstrate the effectiveness of DeepRing in improving accuracy and enhancing model performance across various datasets. However, further development and validation are essential for successful model implementation, further development and validation are essential for successful model implementation. Conclusions: Introduces DeepRing as an innovative solution to address key challenges in predictive modeling, specifically focusing on transparency issues, susceptibility to data manipulation, and fairness concerns. By combining Convolutional Neural Networks (CNNs) with blockchain technology, DeepRing aims to elevate prediction integrity, enhance data security, and promote fairness, thereby contributing to the improvement of ethical considerations, reliability, and accountability in predictive modelling.

Abstract: In this paper, we introduce and study preprocessing signal for speech emotion recognition. The aim of our work is to get pure signal which is created by sampling the signal from speaker. The discrimination between speech and music waves was achieved. A good signal is obtained by using preprocessing then it used for feature extraction. The files we used in this paper are wave-type for male, female and music have sample rate 48000, bit resolution is 16-bits and Mono channel. The Berlin dataset and RAVDESS dataset are used in this work.

Educational certificate counterfeiting is a major global challenge. There is no doubt that addressing both the problem of forgery and the verification of academic certificates is a fundamental issue that deserves research, development, and support at the highest levels. This paper presents a decentralized educational certificate verification system leveraging the Ethereum blockchain and the InterPlanetary File System (IPFS) to combat counterfeiting. Ropsten is used as a real-life Ethereum test network to demonstrate the effectiveness of the proposed system. IPFS is used to store educational certificate files on a decentralised file system. The smart contract is built in the Solidity language, compiled, and deployed using the online Remix IDE. The verification process is supported by scanning a QR code, which retrieves the validating certificate’s information from the Ethereum network in real-time.

The main goal of this paper is to study the degree of the best multiplier approximation of monotone unbounded functions in L_(p,λ_n)-space on the closed interval [-π,π] by means of K-functional, which we represented with, K(f,L_(p,λ_n ),W_(p,λ_n)^1,W ̃_(p,λ_n)^1), defined by the W_(p,λ_n)^1 and W ̃_(p,λ_n)^1 that are referred to during this research. In addition, we have established a set of definitions, concepts and some useful lemmas that are needed in our work.

In this paper, we have improved solutions for two of the Multi-Criteria Machine Scheduling Problems (MCMSP). These problems are to maximize early jobs time and range of lateness jobs times (1//(E_max,R_L ), and the second problem is maximum tardy jobs time and range of lateness jobs times (1//(T_max,R_L ) in a single machine with Multi-Objective Machine Scheduling Problems (MOMSP) 1//(E_max+R_L ) and 1//(T_max+R_L ) which are derived from the main problems respectively. The Local Search Methods (LSMs), Bees Algorithm (BA), and a Simulated Annealing (SA) are applied to solve all suggested problems. Finally, the experimental results of the LSMs are compared with the results of the Branch and Bound (BAB) method for a reasonable time. These results are ensuring the efficiency of LSMs.

The rapid tech growth and widespread internet usage caused a surge in sharing multimedia (text, images, videos, audio) across public networks. Protecting this data is vital, demanding encryption to prevent unauthorized access. Image encryption distorts images for security. This paper highlights encryption's vital role in safeguarding multimedia, especially amid rising internet use and media exchange. It introduces a novel solution: a chaotic three-dimensional system for color image encryption. The study scrutinizes system traits using math software. It employs a new chaotic system to generate a crucial key sequence for pixel scrambling. Utilizing stream cipher encryption enhances security. Extensive security analysis tests its resilience against attacks like histogram and correlation techniques. Results are promising: a fairly uniform histogram, minimal correlation among pixels nearing zero, and entropy close to the ideal. Metrics like NPCR and UACI almost match ideal values, ensuring high security. Experiments confirm its effectiveness in encrypting diverse color images. The approach guarantees a uniform histogram, minimal pixel correlation nearing zero, entropy near the ideal value (8), and NPCR/UACI values close to ideals (99.61191% and 33.41068% respectively).

This paper offers a clear methodology for the characterization of cold atmospheric plasmas and their development. The optical emission spectra of an Ar/O2 plasma jet produced in a plasma jet system at constant flow rates and for various potential discharges between 14 kV and 18 kV revealed that variations in voltage caused a significant difference in the intensity of the Ar/O2 emission. The plasma characteristics of electron temperature (Te), electron density (ne), plasma frequency (fp), Debye length (λD), and the number of particles in the Debye sphere (ND), were estimated using the technique of optical emission spectroscopy (OES). The obtained data are subject to further analysis and discussion. It was determined that potential discharges increased, and an electron temperature increased from 1.34 eV to 1.54 eV. With rising potential discharges, the Debye length decreases while the electron density, plasma frequency, and number of particles in the Debye sphere increase.

In recent years, the Beltrami equation has garnered the attention of numerous researchers for the study of its analytical properties. Therefore, in this paper, we investigate certain properties of an analogue of the Cauchy integral for A(z)-analytic functions, utilizing the analytical properties of the Beltrami equation. Additionally, we obtain the compactness conditions for a family of functions within an A(z)-lemniscate.

In this paper, our purpose is to study the quaternary continuous classical boundary optimal control vector problem (QCCBOCVP) dominated by the quaternary nonlinear parabolic boundary value problem (QNLPBVP). Under suitable assumptions and with given quaternary continuous classical boundary control vector (QCCBCV), the existence theorem for a unique quaternary state vector solution (QSVS) of the weak form (WF) for the QNLPBVP is stated and demonstrated via the Method of Galerkin and the first compactness theorem. Furthermore, the continuity of the Lipchitz operator between the QSVS of the WF for the QLPBVP and the corresponding QCCBCV is proved. The existence of a quaternary continuous classical boundary optimal control vector (QCCBOVC) is stated and demonstrated under suitable assumptions.

In this paper, we developed a secure system for issuing digital signature for digital documents and certificates using message digest algorithm (MD5). The developed system is providing the integrity and authentication for certificates by combining the information of participant and supply them to MD5 algorithm to produce a unique hash key of 32 digits which is hard to guess or attack. The process provides a certificate which allows for the authentication of a document at any time. The proposed system used and tested to produce digital certificate for participant of electronic seminars in Mustansiriyah university which were about 1000 certificate. The results were good and very fair to authenticate certificates and preventing forgery.

Short message services (SMS) represent one of the components of the global communications network and are one of the important developments in communication technologies and communications technology. SMS messages without a password are stored in the SMS server. For the purpose of review and dispute resolution. The security of SMS content cannot be protected because it is transmitted in plain text and is accessible to network operators and employees. Therefore, the end-to-end key is based on encryption and decryption technology can provide SMS security. The security protocols used for SMS security on contemporary mobile devices were examined in this study. SMS security system encryption time affects how well mobile devices work. This shows that security technologies take longer to generate keys and encrypt keys as the key size increases. Due to the limited processing power of mobile devices, large-scale algorithms such as DES, AES, RC4, and Blowfish are not suitable for SMS encryption. SMS may be encrypted using the elliptic curve technique because it provides great security with a smaller key on devices with limited resources, such as mobile phones. And chaotic theory, encryption is simple, fast and secure data encryption. As a result, a combination of elliptic curve algorithm and chaotic encryption algorithm is proposed to achieve a high level of security. In this paper, several tests have been done to compare the algorithms in terms of throughput, power consumption, SMS size, encoding time, and decoding time. The results indicate that the proposed method is better than the comparison method.

In this paper, we have relied on the dominant control system as an important tool in building the group of leaders because it allows leaders to contain less dense areas, avoid local areas and produce a more compact and diverse Pareto front. Nine standard nonlinear functions yielded this result. MaBAT/R2 appears to be more efficient than MOEAD, NSGAII, MPSOD, and SPEA2. MATLAB was used to generate all the results of the proposed method and other methods in the same field of work.

In this study, we propose multi-objective functions which consist of the sum of completion time, tardiness time and earliness time where Ci denoted the completion time of job (i), Ti=max{Ci-di,0}, denotes the tardiness of job (i), Ei=max{di-Ci,0} be denoted the earliness of job (i).This problem is defined by // In this paper, we will present some theoretical analysis discussion, and prove when we have a problem with scheduling n jobs on two identical parallel machines (IPMSP).

In this paper, we introduce the region and the faces poset of shi arrangement that J. Y. Shi firstly introduced it. This is an affine arrangement, each of whose hyperplane is parallel to some"hyperplane of Coxeter arrangement"(Braid arrangement), the degrees and the exponents of this arrangement were found and we prove the shi arrangement is ahyperfactored arrangement when n=3 and not hyperfactored arrangement when n=4 arrangement.

In this paper, tungsten oxide thin films were successfully synthesized by the laser pulse deposition (PLD) method using a pulsed laser (ND-YAG) and wavelength (1064 nm) on a glass substrate at different laser fluencies. The effect of increasing laser fluency, on the optical and structural properties of WO3 nanoparticle thin films, was investigated by UV-Visible spectrophotometer, X-Ray diffraction (XRD), atomic force microscope (AFM) and Scanning Electron Microscope (SEM). X-Ray measurements for all samples of WO3 NPs thin films have shown that by increasing the laser fluencies from 5.175 to 6.369 J/cm2, the intensity of the (2 01) diffraction peak increases due to the film continuing to grow with increased crystallization.

In this research paper, we focus on designing and developing a fully automated gene regulation from cancerous cell heterogeneity using advanced machine learning techniques. There are several modern technologies developed to make DNA sequencing easier and cheaper. Among them, gene regulation produces the longest read sequences and the lengths of the reads are growing day by day. Machine learning technique like Support Vector Machine (SVM) is developed to align these gene sequences. Every technique faced some challenges, but facing the desired challenges introduce some new challenges on the other side. So, no one tool is perfect for every work. The SVM technique is a new aligner tool that does a tradeoff and performs better from different aspects. For the model with the best generator loss, an average maximum validation accuracy of 91.29% was achieved. The gene regulation with SVM is like a mini-map that takes a few times more memory to index the whole genome of a reference sequence. The single-cell data are the main target of SVM. It is shown that it would help the SVM and similar techniques to align better with long insertions and deletions of single-cell gene regulation. Single-cell data is run against the well-known reference sequence and a randomly generated synthetic reference.

In this work, we introduce some common fixed points theorems type rational contractions on generalized Banach space. The provided theorem is a generalization and an extension of many well-known theorems; we present a few examples to illustrate the validity of the results obtained in the paper.

In this paper, we designed a new efficient stream cipher cryptosystem that depends on a chaotic map to encrypt (decrypt) different types of digital images. The designed encryption system passed all basic efficiency criteria (like Randomness, MSE, PSNR, Histogram Analysis, and Key Space) that were applied to the key extracted from the random generator as well as to the digital images after completing the encryption process.

In this paper, our purpose is to study the classical continuous constraints boundary optimal triple control vector problem dominating nonlinear triple parabolic boundary value problem. The existence theorem for a classical continuous triple optimal control vector CCCBOTCV is stated and proved under suitable assumptions. The mathematical formulation of the adjoint triple boundary value problem associated with the nonlinear triple parabolic boundary value problem is discovered. The Fréchet derivative of the Hamiltonian is derived. Under proper assumptions, both theorems are granted; the necessary conditions for optimality and the sufficient conditions for optimality of the classical continuous constraints boundary optimal triple control vector problem are stated and proven.

The present article proposes an exact algorithm for the single-machine scheduling problem to minimize the sum of total completion times, range of lateness and maximum tardiness on a single machine (1/ /(∑ C_(σ_j + R_L + T_max)), where machine idle time is prohibited. In this paper, one of the multiobjective function problem for single criteria on just one machine is being studied. To obtain the optimal solution for the suggested problem, we propose to use Branch and Bound method (BAB) depending upon some dominance rules. This exact method used new technique to obtain three upper bounds (UB) and single lower bound (LB). The proposed BAB method proved its sufficiency by the practical results for n ≤ 15 in a reasonable time. Lastly, we proved a theorem as special case for our problem.

In this paper, studied the types of (k, r)-arcs were constructed by action of groups on the three-dimensional projective space over the Galois field of order eight. Also, determined if they form complete arcs or not.

The purpose of this paper is present some operators by using polynomials operators of type G_n (f,x),g_n (f,x),L_n (f) and M_n (f), to get the degree of best one- sided multiplier approximation of unbounded functions by algebraic polynomials in L_(p,φ_n ) (X),X=[0,1] , by τ〖(f,δ)〗_(p,ψ_n ).

In this paper presents the R reliability mathematical formula of (3+1) Weibull Cascade model. The reliability of the model is expressed by Weibull random variables, which are stress and strength distributions. The reliability model was estimated by six dissimilar methods (ML, Mo, LS, WLS, Rg and Pr) and simulation was performed using MATLAB 2012 program to compare the results of the reliability model estimates using the MSE criterion, the results indicated that the best estimator among the six estimators was ML.

In this paper, our purpose is to study the classical continuous boundary optimal triple control vector problem (CCBOTCVP) dominating by nonlinear triple parabolic boundary value problem (NLTPBVP). Under suitable assumptions and with given classical continuous boundary triple control vector (CCBTCV), the existence theorem for a unique state triple vector solution (STVS) of the weak form W.F for the NLTPBVP is stated and demonstrated via the Method of Galerkin (MGa), and the first compactness theorem. Furthermore, the continuity operator between the STVS of the WFO for the NLTPBVP and the corresponding CCBTCV is stated and demonstrated. The continuity of the Lipschitz (LIP.) operator between the STVS of the WFo for the QNLPBVP and the corresponding CCBTCV is proved. The existence of a CCBOTCV is stated and demonstrated under suitable conditions.

Text summarization is an important research topic in the field of information technology because of the large volume of texts, and the large amount of data found on the Internet and social media. The task of summarizing the text has gained great importance that requires finding highly efficient ways in the process of extracting knowledge in various fields, Thus, there was a need for methods of summarizing texts for one document or multiple documents. The summarization methods aim to obtain the main content of the set of documents at the same time to reduce redundant information. In this paper, an efficient method to summarize texts is proposed that depends on the word association algorithm to separate and merge sentences after summarizing them. As well as the use of data mining technology in the process of redistributing information according to the (K-Mean) algorithm and the use of (Term Frequency Inverse Document Frequency TF-IDF) technology for measuring the properties of summarized texts. The experimental results found that the summarization ratios are good by deleting unimportant words. Also, the method of extracting characteristics for texts was useful in grouping similar texts into clusters, which makes this method possible to be combined with other methods in artificial intelligence such as fuzzy logic or evolutionary algorithms in increasing summarization rates and accelerating cluster operations.

The primary aim of this paper is to define new concepts, A homogenous system of difference equations is called -semi homogenous of order if there exists a non-zero matrix

Contamination feedstuffs with fungi or their metabolites toxins poses considerable hazard to public health and animal welfare. The information on mycotoxins identified from a variety of feedstuff in 2021 (soyabean, maize, fish meals, and poultry pellets) was retrieved from archive papers documented in the Centre of Standardization and Quality Control/Department of Agriculture. A total of 1325 samples feedstuff were examined by this Centre using the direct ELISA test to detect aflatoxins, ochratoxin, and trichothecene. The aflatoxin was identified in 67 (5.05%) samples followed by ochratoxin in 52 (3.92%) samples and Trichothecene (T2) in 50 (3.77) samples. Additionally, the results were showed the co-infection/co-occurrence of mycotoxins from positive samples of soyabean, fish meals, and poultry pellet, although this contamination within acceptable level. Only two samples of poultry feed were determined to have contamination levels above the acceptable limit, as 21ppb with aflatoxins and 19ppb with ochratoxin contamination. The moisture levels were also measured for these commodities by NIR apparatus. From statistics outputs, the squared correlation coefficient (R2) did not share too much variability between moisture and degree of contamination with three mycotoxins identified. The study concluded that mycotoxins remain to be a concern for global health, and their residues in animal feed are important in terms of health safety standards that propose adhering to food chain regulations in commercial markets.

In this paper, Bernoulli's polynomials approach is employed for solving approximately linear Fractional Fredholm integro-differential equations via Petrove-Glerkain method. The Fractional derivatives are described in the sense Caputo. The approximate solution is compared with the exact solution to confirm the validity and efficiency of the method to a same as before. Some illustrative examples are presented.

In the last few years, and due to the vast widespread of social media applications, texts have become more important and get more attention. Since texts, in general, are carrying a lot of information that can be extracted and analyzed. Several researchers have done significant works in text classification. Within different scripts such as English and other western languages, several challenges and obstacles have been addressed with such a field of research. Regarding the Arabic language, the process is different from other vital languages since Arabic is considered an orthographic language that depends on the word shape. It is not easy to apply the standard text preprocessing techniques since it affects the word meaning. This paper evaluates Arabic short text classification using three standard Naïve Bayes classifiers. In our method, we classify the thesis and dissertations using their titles to perform the classification process. The collected dataset is collected from different repositories by using standard scrapping techniques. Our method classifies the document based on their titles to be placed in the desired specialization. Several preprocessing techniques have been applied, such as (punctuation removal, stop words removal, and space vectorization). For feature extraction, we adopt the TF-IDF method. We implemented three types of Naïve Bayes classifiers which are (Multinomial Naïve Bayes, Complemented Naïve Bayes, and Gaussian Naïve Bayes). The study results showed that Complemented Naïve Bayes Classifier proposed the best performance with (0.84) of accuracy for the testing phase. The results of the study are promising to be applied with different short text classifications.

The aim of this paper is to study Z-transform to solve non-linear difference equations, after converting them to linear difference equations by one of the conversion methods. This is because the z-transform cannot be directly applied to the nonlinear difference equations.

The objectives of this paper are to use micro-X-ray fluorescence spectrometry (μ-XRF) and portable X-ray fluorescence spectrometry to specify the quality and element percent content of Sasanian and Parthian artwork samples: glasses, metals, and ceramics found in various regions of the Garmian area to determine and characterize the element and material compositions of the studied samples. The metallic models (L, M) are made of iron, (O) brass, (N.R) bronze, and (W, Y) silver, according to our findings. Soda ash makes up the majority of the glass samples (Si, Na, Ca>1%, MgO, K2O>1%). Sample J might be soda-lime glass because of the low Mg and K content (

Vegetation cover is considered one of the most important factors that affect weather, climate, and the environment. This paper aims to study the correlation between land surface temperature and the Vegetation Indices using Landsat data in Duhok Governorate, Iraq. Landsat-8 images were taken for December, April, July, and October in 2019. Geographic Information System ArcGIS 10.2 package has been used to calculate the results. The Normalized difference vegetation index NDVI, Green ratio vegetation index (GRVI), and land surface temperature (LST) have been computed. The results showed that were a strong positive relationship between vegetation indices during winter, spring, summer, and fall seasons. The correlation coefficient values ranged from (0.9) in winter, (0.96) in spring, (0.95) in summer and (0.89) in autumn seasons. Also, the results showed a strong inverse correlation among LST and NDVI, GRVI indices during winter, spring, summer, and autumn seasons. The strongest correlation between land surface temperature and the Vegetation Indices was in the Spring Season. These correlations can be used to study vegetation health, drought.

With the increased use of information technology, many financial services are available to users at their fingertips. However, this led to many fraud transactions. Automatic fraud identification and detection could improve the user experience and security of online transactions. Using machine learning algorithms, it is possible to detect fraud transactions. Machine learning algorithms have the ability to find the hidden implicit pattern and data relationships from a large dataset. Hence, using this algorithm is possible to detect the outlier from all transactions, which can help in determining the fraud transaction. In this paper, the APRIORI algorithm and Support Vector Machine are used to detect fraud transactions in credit cards via developing a secure web application service enforced the security by standard metrics. We compare the result with the other existing machine learning algorithms. We observed that the accuracy of fraud transaction detection is higher in the proposed algorithm more than 94.56, and the false fraud transaction detection is less than the fraud detection based on the Hidden Markov Model.

In this paper, we constructed new arcs in the three-dimensional projective space over GF(13) of degrees 2, 3, 4, 5, 6, 7, 10, 11, 14, 15, 18, 19, 23, 28, 30, 47, 55, 98 and sizes 2, 4, 5, 7, 10, 14, 17, 20, 28, 34, 35, 68, 70, 85, 119, 140, 170, 238, 340, 476, 595, 1190. These arcs are classified to complete and incomplete arcs. Also, the incomplete arcs are extended to complete arcs.

In this paper, a proposed carbon dioxide Gas Sensing System of high precision, rapid reaction, compact size and low power consumption rate is presented based on the non-dispersive infrared (NDIR) measurement. This system used to determine CO2 gas concentration in air; it consists of the single broadband light source, U-shape tube optical path cavity as gas cell, thermopile detector, and microcontroller circuit. This study investigates the efficiency of the U-tube optical path cavity at CO2 gas concentrations ranging from (0-5000) ppm. The obtained results show that it has the better thermal response compare to the linear tube and exhibits high sensitivity by change the transmitted light intensity into analog voltage. The proposed system design can be used as an environmental monitoring sensor.