bluuebunny/crossref_metadata_2025_split huggingface dataset:
Using Cucumber Plants Leaves A Cover To Hiding Encryption Text
Authors: Abdullah Ahmed Saadi , Sleman Walead Kaled , Waleed Mohammed 
Published: March 2021

AbstractThe article presented a way to increase the efficiency of hiding information by relying on the leaves of the cucumber plant and using it as a cover to hide the information after applying a set of digital image processing techniques to this image. As for the text to be hidden, the text is initially encrypted based on an innovative cryptographic algorithm, three criteria were used to measure The efficiency of the algorithm is psnr, mse, rmse.
An Image of Encryption Algorithm Using Graph Theory and Speech Signal Key Generation
Authors: Abduljaleel Iman Qays , Abdul-Ghani Samaher Adnan , Naji Huda Zaki 
Published: March 2021

Abstract
In this paper, a color image of encryption algorithm used a graph theory has been proposed. The proposed algorithm depends on the audio files as a basis for exploiting a set of keys for encoding color images. The key generation system was built by passing the audio signal in several stages based on the graph theory. The results revealed that the proposed algorithm has generated the encrypted images with uniform distribution in pixel histograms with information entropy closes to 8, which resists different attacks. The comparison experiments with other recent algorithms were performed. The statistical results show that the proposed algorithm has a strong security against attacks.
Classification of Arabic Documents depending on Maximal Frequent Itemsets
Authors: Hamid Zeyad , Khafaji Hussein K. 
Published: March 2021

Abstract
In this paper we introduced techniques for classifying Arabic documents depending on association rules built from maximal frequent itemsets. Parallel Maximal Itemset Miner Algorithm (PMIMA) adopted several conditions to prune search space parallelly introduced for extracting maximal frequent itemsets. Rule length, rule weight and rule majority are three classification methods exploited to classification Arabic documents. Comparing with classification results obtained depending on all frequent itemsets extracted by Apriori, we proved efficiency of ours approach.
Design and Develop an Attendance System Based on Fingerprint and Arduino Board
Authors: Abdulkadhim Ekhlas Ghaleb 
Published: March 2021

Abstract
The academic attendance of students largely influences their acquired knowledge, grades, and skills and is of paramount importance. The present study aimed to reinforce a fingerprint identification system to be applied in a database. Fingerprinting is an efficient and rapid technique for attendance checks as it represents the uniqueness of humans and is easily available. Fingerprint sensors have benefited from this exclusivity for the automatic identification or recognition of individuals. To this end, we designed and developed an attendance system, the main components of which were a Fingerprint reader and Arduino board (microcontroller) for the insertion of the records into the database. As a result, the performance evaluation of students was facilitated by the recorded attendance in an accurate, efficient manner with the least possible error, as the results of testing this system was with an average of 98.833 %, as well as the improved academic performance of students as they must attend all the sessions and cannot avoid classes.
Applying the Artificial Neural Networks with Multiwavelet Transform on Phoneme recognition
Authors: AlKhafaji Baydaa Jaffer , Salih May A. , Shnain Shaymaa AbdulHussein , Rashid Omar Adel , Rashid Abdulla Adil , Hussein Moheeb Tariq 
Published: March 2021

Abstract
There are several advantages of Phoneme recognition. identification. It is easier to use speech for data entrance spoken communication for data ingress than other tools. It allows writing user-friendly data entrance exploiter-friendly data ingress programs. There are several difficulties in speech voice communication recognition. One of these difficulties is noise. Variability in speech is another problem. Even the speech of same speaker varies. The ability of artificial neural networks to generalize and optimize more quickly than some conventional algorithms algorithmic rule has been observed in different areas of research inquiry such as speech and pattern convention recognition, financial forecasting prognostication, image data compression and noise reduction simplification in signal processing. Neural networks take advantage of the redundancy incorporated in their distributed processing structures the proposed system depends on Artificial Neural Networks Network as decision making qualification algorithm to find the best match peer for the tested phonemes. Phoneme. The data used in this project are Arabic phonemes language phoneme stored as 8-bit mono infectious mononucleosis 8000Hz PCM WAVE Sound Auditory sensation file. The results showed that the accuracy of the proposed system is 98% recognizes the phonemes efficiently.
Study of Some Factors Affecting on the Chickenpox Cases by Using the Partial Linear Regression Model
Authors: Mahdi Nabaa Naeem , Raheem Auday Taha , Rasheed Aseel Abdul Razzak 
Published: March 2021

AbstractChickenpox is classified as a transmission disease, especially young ages from three months to 15 years old. This study clarifies the effect of the area, population, and the number of the health centers on the number of cases of chickenpox disease in the Rusafa district, Baghdad, Iraq. We use the Partial Linear Model (PLM) that divides the independent variables into two parts (parametric and non-parametric). Moreover, choosing the best model that represents data of the chickenpox disease, using criteria (R2, Bic, Aic) from six models. The results of the study show a positive relation between the number of cases and number of health centers.
A Review on Distributed Blockchain Technology for E-voting Systems
Authors: Sahib Rihab H , Al-Shamery Eman S. 
Published: March 2021

Abstract
Election is an important event in all countries. Conventional voting suffers many issues, such as cost of time and efforts needed for tallying and counting results, cost in papers, arrangements and all that it takes for a voting process to be achieved. Many countries such as Australia, Belgium, Brazil, Canada, Estonia, France, Germany, India, Italy, Namibia, the Netherlands, Norway, Peru, Switzerland, the UK, Venezuela and the Philippines considered online e-voting systems, but the traditional e-voting systems suffer a lack of trust, it is not known if a vote is counted correctly, tampered or not. The voter has no guarantee that his/her vote is considered as they voted in elections, it’s a lack of transparency. A solution is e-voting systems based on blockchain (sometimes referred as Distributed Ledger Technology (DLT)) has now turned to be promising for what properties it offer, such as, privacy, security, transparency, accuracy, decentralization in which no central control exist, and most of all, creates an immutable system, where citizens are allowed to vote from their location by using digital devices (smart phones, computers, electronic voting machines). Also, due to the COVID-19 pandemic, many technology applications are heading towards systems with all these properties, at the same time, maintaining social distancing. This review introduced many different ideas for implementing e-voting systems based on Blockchain and how the users (voters and candidates) interact with the system showing the voting process from the first step of registration to authentication till showing the final results. At the end of this review we will illustrate a table that contain all mechanisms used in the papers involved that covers the most important requirements needed for every e-voting system based on blockchain or Distributed Ledger Technology (DLT).
Bifurcation of Novel Seven-Dimension Hyper Chaotic System
Authors: Zghair Hayder Kadhim , Mehdi Sadiq A. , Sadkhan Sattar B. 
Published: March 2021

Abstract
In this paper, introduced a novel seven dimensions (7D) nonlinear hyperchaotic system in third-order. A chaotic behavior that has twelve positive parameters for novel 7D hyperchaotic is analyzed through calculating the Lyapunov exponent, attracter of the system, fractional dimension, influence parameters, dissipative, bifurcation path, and phase portraits. It is well known that one of the chaotic definitions is the novel 7D chaotic if it satisfies positive Lyapunov exponent at each point on its domain (eventually periodic). The results from the numerical analysis of Lyapunov exponents, bifurcation have shown that there are periodic dynamic behaviors, quasi-periodic, the existence of chaotic attractors, and hyperchaotic for our analyzed to the proposed system. Also, some complex dynamic behaviors are discussed, such as equilibrium stability, Besides, discuss when a parameter changes a properties phase portrait change also. The dynamics of the proposed novel 7D hyperchaotic simulated and implemented using the Mathematica program provided qualitatively and it illustrated phase portraits.
A Proposed Intelligent Features Selection Method Using Meerkat Clan Algorithm
Authors: Jameel Noor , Abdullah Hasanen S. 
Published: March 2021

Abstract
The feature selection process stand to select the subset of feature from the set of datasets to get the relevant an important features and remove irrelevant features. The feature selection types are supervised, unsupervised or semi-supervised. The feature selection methods are divided into: traditional methods such as Correlation and Information Gain or others and intelligent methods such as fuzzy logic, or use the swarm intelligence methods in feature selection such as Ant colony and Bees colony. This paper proposes an Intelligent Features Selection method based on Meerkat Clan Algorithm (IFS\MCA) system, when it used the modern MCA as first time to use the algorithm in feature selection to select the best subset of feature. This proposal used four set of dataset which as (Fri_c4, Sonar, Scene, Satellite), the efficiency of the proposal in feature selection is powerful and high accuracy when comparing with other standard methods in feature selection which as Correlation and Information gain when use the same set of dataset. The proposed IFS\MCA system uses the Mean Absolute Deviation (MAD) as a proposed choice as a fitness function (which is used as a first time with feature selection process).
Kerberos Authentication for Big Data Applications on Cloud Environment
Authors: Albaldawi Wafaa S. , Almuttairi Rafah M. 
Published: March 2021

Abstract
The large set of User, Sensor, Medical, and Enterprise data can be collected and obtaion big data. Therefore, there is a need for platform for storing, managing and distributing it across multiple nodes. In the paper, we represent approach which is based on Kerberos in Hadoop distributed file system. It is used to access the right blocks of data by the authorized user only. To provide a security in Namenode, Ticket Granting Ticket and Service Ticket have been used for that. Kerberos installation in server and clients are illustrated in details.
The Fear Effect on a Food Chain Prey-Predator Model Incorporating a Prey Refuge and Harvesting
Authors: Alabacy Zina Kh. , Majeed Azhar A. 
Published: March 2021

Abstract
In this paper, we investigate the impact of fear on a food chain mathematical model with prey refuge and harvesting. The prey species reproduces by to the law of logistic growth. The model is adapted from version of the Holling type-II prey-first predator and Lotka-Volterra for first predator-second predator model. The conditions, have been examined that assurance the existence of equilibrium points. Uniqueness and boundedness of the solution of the system have been achieve. The local and global dynamical behaviors are discussed and analyzed. In the end, numerical simulations are confirmed the theoretical results that obtained and to display the effectiveness of varying each parameter on our proposed model.
Nearly Monotone Neural Approximation with Quadratic Activation Function
Authors: Almurieb Hawraa Abbas , Bhaya Eman Samir 
Published: March 2021

Abstract
Quadratic functions give good rates of approximation when used as activation functions of feedforward neural networks. Also, monotonicity is important to describe the function behavior, so the behavior of its constrained approximation. Previously, the degree of approximation by feedforward neural networks with quadratic activation function is proved to be within no less than the second order modulus of smoothness. In this paper, we discuss whether the improvement of the above estimates for Lebesgue integrable functions is possible or not. By nearly monotone approximation, it is possible to talk about a higher order modulus of smoothness, while it is not for just monotone functions. We get a nearly monotone function approximation by splitting the interval [0,1] into a partition with infinitely small lengths and then excluding intervals near the endpoints of the partition’s subintervals. However, counter examples cut hope for any more improvement outside that restricted interval. All the results are proved in the Lp-space with p < 1.
Performance Analysis of Least Significant Bit Based Watermarking Technique Under Various Types of Attacks
Authors: Hasan Afkar Ali , Jawad Majid Jabbar , Naser Mohammed Abdullah 
Published: March 2021

AbstractDigital information transferred through internet should be protection from unauthorized and attack resource using one of the information security system method, one of these methods was digital watermarking was used in order to prevent information from various types of attack adversary since it satisfies all security system requirements (authentication, integrity and confident). Digital watermarking is used digital image for several purposes such as authentication, copyright, and many purposes. This paper we embedded (number of bits) MSB of watermark image in the (number of bits) LSB of cover image by proposed embedding algorithm, where the ratio of appearing information of the watermark in the watermarked image depends on a number bits embedded. Such that increasing the number bits increase the information display. The performance of the algorithm for watermarking and quality of reconstructed image have been measured in terms of MSE and PSNR. This paper produced performance analysis of image watermarking technique depend on least significant bit against several attacks (Gaussian, salt and pepper noise, Poisson and Speckle). The result of the attack appears that salt and pepper attack give best result than other types when it applied on the original image and watermarked image. Simulation results show that best results were achieved against Salt and Pepper attack in terms of less MSE and high PSNR. MATLAB language is used for implementing the suggested Algorithm.
On S-Prime and S-Semiprime RΓ-Submodules of RΓ-Module
Authors: Zyarah Ali Abd Alhussein , Al-Mothafar Nuhad Salim 
Published: March 2021

Abstract
Let R be a Γ-ring and G be a RΓ-module. Aproper RΓ-submodule E of G is said to be S-prime (S-semiprime) RΓ-submodule of G whenever μ(K) ⊆ E ( μ(m) γ μ(m) E ), for some K be a RΓ-submodule of G, where End (G), y Γ and m G, then K ⊆ E or M(G)⊆ E ( μ(m) E). The reason of this paper and we give some basic properties and characterizations of S-prime and S-semiprime submodules.
Usage of OSPF Convention in System Designed in Republic of Iraq
Authors: Ibrahim Sura Khalil , Jebur Zainab Taha 
Published: March 2021

Abstract
OSPF is a very important internal entryway protocol that employed in web layer of TCP/IP model and in network layer in OSI model. OSPF is employed in application of current networks like impromptu wireless and mobile communication systems, in ISP, enterprise networks in colleges, hospitals…etc. it additionally employed in management plane of SDN. OSPF can management on call of that have the shortest path of network branches looking on their weights. Principle work of OSPF protocol verify the shortest path by checking link state of network. Also, principle of this protocol, it divides identical network into areas (sub networks).during this paper, OSPF network has one space referred to as (area 0), that has 6-Routers distributed among cities on Iraq’s map. MATLAB (2017b) and GNS-3 (2.1.3) softwares area unit wont to calculate theoretical and experimental results severally. The results evidenced that the most effective path that has the low weights and time period. These results additionally evidenced that if the shortest path is down, it may be used the opposite link (back up) within the network.
A Novel Approach for Detection Insider Attacker Using Body Language
Authors: Mohammed Mohammed Abdallazez , Kadhem Suhad Malallah , Maisa’a Abid Ali K 
Published: March 2021

Abstract
One of most important challenges in cyber security is detecting the insider attacker (a person or an employee with an authorized access to resources and data of an organization then uses that access - either wittingly or unwittingly - to harm organization security). This paper propose approach to obtain early indicator to insider attacker before doing the crime. The previous security systems focus on the technical anomaly of an employee to discover the insider attacker and can’t discover it, if there isn’t technical anomaly. This paper attempt to discover insider attacker when there isn’t technical anomaly, Where presented body language-based approach to give earlier alarm of insider attacker. By using three of negative body language gestures (Cross Arms, Clasped Hands, Covering the Mouth) which referred to feeling of insecure, ready for an attack, doubt and a lack of self-confidence, these feelings are the closest to the feelings of the internal attacker. These gestures obtained by use skeleton features from video stream provided by Orbbec Astra Pro camera after passed to rule based classifier to recognize each one of the three body language gestures. Then determined the degree of trust based on the duration of the gesture and the number of occurrences of the same gesture or different gestures and depending on the degree of trust, the organization is alerted to the questionable employees. The test performs on ten of employees, four insider attackers were planted among them, and the results show 70% accuracy of detects the insiders, this approach will detect insider attacker before started his malicious work.
Sobolev Inequalities for Functions on Graphs
Authors: Bhaya Eman Samir , Flaih Zainab 
Published: March 2021

Abstract
The aim of this paper is to study the Sobolev inequalities when 0 <
p
< 1. Sobolev spaces defined by the Russian mathematician Sorgi Sobolev. The need for these spaces that some results are found in these spaces rather than the spaces of continuous functions. Sobolev and some authors proved Sobolev inequality in the cases p= 1 and then p > 1. Here we prove Sobolev types inequalities in the case 0 < p < 1. An infinite dimensional Sobolev inequality for expander is also proved. Also we introduce estimates for Banach-Mazur distance between the spaces Sp(G) and Z- using Cheeger constant.
Auto Transition Function in RADG
Authors: Habeeb Sundus. Q. , Albermany Salah A. K. 
Published: March 2021

Abstract
The main problem of RADG (Reaction Automata Directed Graph) is the fixed design of the graph. The purpose of this paper is to develop the transition function from fixed design to dynamic design, the dynamic design based on a key between sender and receiver in addition to some rules, the new design is more efficient and fairly distributed between standard states and reaction states, that design keeps the main aspect of RADG which gives more than one ciphertext to the same plaintext and adds high level of security to the wireless network.
Video Tampering Detection Using Difference-Hashing Algorithm
Authors: Sujatha G. , Hemavathi D. , Sornalakshmi K. , Sindhu S. 
Published: March 2021

Abstract
Videos plays an important role in the judgement of many criminal cases. It can be considered as an evidence in every step in the criminal justice process. Since it is involved in the judgement, the integrity of the video is very much important. If anything gets tampered in the video, it leads to misconception in the process. Video tampering detection is a technique of finding whether the video content is modified or not. Alteration of video contents is rising speedily because of increasing video procurement gadgets and enormous programming devices to alter the video content. This integrity check can be done by either active or passive techniques. Along these lines our zone of worry in our research work is to display our perspectives on various passive video tampering detection techniques to check its correctness. Passive techniques are assembled into ensuing three arrangements relying upon the kind of counterfeiting. There are different methods to perform video tampering detection but passive methods prove more effective in terms of maintaining the originality of the video. Even in passive methods, hashing has been the sort after approach because of its accuracy and so we have adopted Difference hashing algorithm (D-Hash) to perform tampering detection.
The study of determining the levels of radon gas concentrations (soil, water and plants) in the areas exposed to military operations in Suq Al-Shuyoukh district, south of Thi-Qar province, Iraq
Authors: Mathloom Ahmed R. , Alkhafaji Mohammed Hashim , Al-Hachami Ali Abood 
Published: March 2021

Abstract
In this study, the radon concentration of Al-Khamisiyah (A) stores and the adjacent residential areas (Al-Twirat area (B), and the Al-Khamisiyah (C) residential area) located in the southwest of Dhi Qar governorate were measured by five samples for each area for the study models (soil, water, Plants) by using the alpha particle counting technique emitted from radon in the nuclear trace detector (CR-39). The study included three parts, the first part is to measure the radon concentration in samples from the soil and with depths of 60 cm, 15cm, 2cm)) for areas (A, B, C) where the highest concentration was at 2cm depth and the lowest concentration was at the depth 60cm and for all study areas, the highest concentration was in Region A, for all depths, and the lowest concentration in region B. The second part included determining the concentrations of radon gas in the waters of passing rivers in regions (A, B, C), where the highest concentration was in area A and the lowest concentration in region B. As for the third part, it included determining radon concentrations in some types of plants that grow in those regions (A, B, C) such as reeds, sedge and brains, where the highest concentration was in the reed plant and the lowest concentration in the clematis plant and for all areas of study. Finally, we would like to point out that the current study is considered one of the important and vital studies because it is related to the health and safety of humans.