bluuebunny/crossref_metadata_2025_split huggingface dataset:
Augmented Reality Technology in Education
Authors: Abd Al-hassan Hind Adai , H.Suad Jamila , H. Ali Hatem 
Published: November 2020

Abstract
Augmented reality technology has entered the field of education, and augmented reality is one of the innovations of technology. The educational institutions that allow uniqueness and enrichment of educational jobs through feeding them with many different sources and alternatives, which constitute an integrated combined methodological unit aimed at achieving ideal learning that is characterized by a large degree of effectiveness, efficiency and mastery and supports the learning process through its new and different by adding audio, 3D, and video. This technology transmits information by adding a new virtual image (audio visual information) to the still image (the real world) and this allows the learner to interact with this technology by dealing with additional information or objects that are displayed in the real world. In this paper, the proposed method for promoting and supporting the traditional method of teaching and converting difficult and complex materials into easy materials is presented easy to understand and memorize, which is called Technology Enhanced Learning (TEL). In this technique is produced virtual elements such as explanatory video, audio and three-dimensional shapes, these elements are stored in the database and linked to the note in the study material created when the learner focus the phone camera towards the mark, then camera picks up the mark, and opens the default elements on the phone screen.
Analysis of Criminal Spatial Events in GIS for predicting hotspots
Authors: F. Mohammed Abbas , R. Baiee Wadhah 
Published: November 2020

Abstract
The crime rate increasing in developing countries cause of the unequal distribution of psychological, economic situation. This research aims to identify the crime mapping and investigate the hotspots and analyzing the spatial crime dataset and the predict of Spatio-temporal hotspot in Baltimore city for a period from 2012 to 2018. Analyzing crime data using data mining algorithms and The Geographic Information System (GIS) of Geographic dataset visualize and it possible for law enforcement to detect spatial crime patterns map easy and flexible and different analysis to identify the crime hotspot region efficiently. analysis crime hotspot using GIS is a useful way to the recognition for crime pattern and predicting hotspot over spatial correlation, analysis spatial data and revile crime pattern future detection. using spatial correlation, the G* statistic has been done with hotspot analysis the Getis-Ord Gi* to find the result of the spatial statistics pattern. analysis the crime to predict hotspot uses spatial variation and density crimes for clarifying the positions of statistically significant crime predict hotspots and cold spots and GIS interpolation method is used for more efficient visualization. This research using Grid network hotspots are applied to the crime data of Baltimore, Maryland state to recognize the hotspots for crime data like Shooting, Homicide and Assault by threat.
Evaluation of Transfer Learning with CNN to classify the Jaw Tumors
Authors: Ismael Ahmed Khalid , Khidhir AbdulSattar Mohammed 
Published: November 2020

Abstract
Artificial Intelligence” (AI) This term refers to the idea that the machines can perform human tasks. Recently, researchers, professionals and companies around the world introduce deep learning and image processing systems that can analyze hundreds of X-Ray and Computer Tomography (CT) images rapidly to speed up the diagnosis of medical image and help to contain them. Dental diseases analysis is among the most innovative research fields, offering diagnostic and decision-making facilities for a variety of diseases, such as oral and maxillofacial diseases. Inside this paper, we present a comparison of recent architectures of the Deep Convolutional Neural Network (DCNN) for the automatic classification of two diseases depending on transfer learning with fined tuned using a pre-trained network (VGG16, VGG19). The proposed work was tested using a small scale X-Ray panoramic dataset containing 116 images (58 ameloblastoma and 58 Complex Odontoma). As a result, we can assume that the pre-trained network (VGG19) demonstrates highly satisfactory results with a rate of increase in the accuracy of training and validation. Unlike CNN, pre-trained network (VGG16) demonstrates less performance when a small image dataset is available.
Selecting Best CPU frequency for energy saving in cluster using genetic algorithm
Authors: A. Abdulazeez Zainab , B. M. Fanfakh Ahmed , H. Alwan Esraa 
Published: November 2020

Abstract
Dynamic voltage and frequency scaling (DVFS) is a technique mainly used for reducing the consumed energy of computer’s processor. Its only drawback detracting the performance of parallel application when executing them over parallel platform. However, genetic algorithm is introduced and applied in a heterogeneous cluster architecture for modeling the best trade-off between the energy saving and performance degradation of the parallel application in the same time. The suggested algorithm selects the best frequencies vector to achieve that targets by offering equal trade-off between them. The genetic algorithm simultaneously gives minimum energy consumption and minimal performance degradation via its objective function. All experiment will apply using SimGrid simulator. The experiments show that the algorithm reduces the energy consumption of the message passing application by (24% with 8000 problem size and 22% for 4000 problem size) and in almost cases improve the application performance up to 3%.
A Comparison Study for Intelligent Wheelchair Based on MEMS Sensors
Authors: Satar Al_Dosary Duaa Abdul , M Ali Alheeti Khattab , Sleibi Al-Rawi Salah 
Published: November 2020

Abstract
Today, the security of the system must be improved. A new approach is proposed that achievements the Integrated Circuit Metrics (ICMetric) technology to support identification of devices. ICMetric is a novel technology that generates the identification of devices based on the internal behavior of device features. In this paper, a comparative study is presented between two of our systems. These protection systems are designed to provide protection systems for intelligent wheelchairs. However, we proved that node identification can be provided by utilizing the three types of MEMS sensors. Extracted readings are acquired from the sensors and analyzed mathematically and statistically to provide an ICMetric basis that used to introduce identification of the device. Simulation results show that the proposed system can increase authentication and security.
Fuzzy Association Rule Classification System For Human DNA profile Identification
Authors: H. Faleh Najah , H. Karidi Karim 
Published: November 2020

AbstractRecently, numerous identification methods are adopted in human identification systems particularly for forensic affairs. These methods are used to reduce the human efforts, related errors, cost, and consumed time in addition to increase the accuracy of human identification systems. The definition of STR DNA profile of a person’s, is associated to the reduction or detection of criminal investigation associated to the identification of the suspect, or to an investigation in counter terrorism as well as in the National Security Service. DNA is used for disaster victims or suspected individuals as a main means of identification. It possesses a high degree of verification in the courts when there is biological evidence, and is also used to identify persons accused and innocent people in criminal investigation with incredible accuracy. This thesis proposes a forensic human identification system based on Deoxyribonucleic Acid (DNA) classification. This system is depend on the concept of fuzzy logic and data mining in identification, that play role important in established a plenty of effective applications in DNA profile analysis and human identification, and reduce error or prevent and so they are chosen for their high accuracy. The main contribution of the presented system is, used association rules for classification the DNA motifs in addition to the fuzzy inference to correct errors, that can offer a high range of useful information. This information is permanently used to solve the crimes and identify damaged bodies. Additionally, this overcomes the lack problem in database information. It is important to note that the proposed system includes DNA based human identifications to cover all investigation cases. The aim of this thesis is to build a forensic human identification system that uses data mining techniques to access dataset by enforce particular algorithms for discovering advisable information or good patterns from present datasets for certain objective. To improve the data mining work, fuzzy logic is used to increase the flexibility for supporting DNA profile forensic human identification in making decisions. It utilizes sixteen Short Tandem Repeats (STRs) DNA loci used in identification methods for Population. It is important to note that the proposed system has been verified In terms of matching of provided samples with the samples stored in the database through conducting several experiments. The results were satisfactory and characterized by large percentage and high accuracy. Finally, performance of this system is evaluated and in turns the proposed system proves its capability in forensic human identification and scalability to handle huge amounts of data.
PROPOSED KNOWLEDGE MANAGEMENT CONCEPTUAL MODEL TO ENHANCE TEACHING ACTIVITIES THROUGHOUT WEB 2.0 TECHNOLOGY FOR ACADEMICIANS
Authors: Al-Sulami Zainab Amin , Hashim Hayder Salah 
Published: November 2020

AbstractIn the era of information technology, knowledge management became urgent need for raising the competitive advantage level. Universities considered as knowledge intensive base organizations. The knowledge are embedded in the academicians minds are sharing within students throughout various teaching activities. A valuable amount of knowledge that accumulated from academicians need to collected for sharing among the academicians community. The successful knowledge management processes of academician experiences lead to enhance the teaching activities. The learning process enhance by assisting academician to learn from each other and product high quality teaching activities. Most of academician’s knowledge is faded due to the absence of standard system that could collect and share the teaching experiences. This research proposed knowledge management conceptual model that can enhance the knowledge processes of acquiring, storing, sharing, and reusing teaching experiences. Data collected by interviewing academicians from Iraq universities and obtaining the required data. The findings deployed to develop knowledge management model that could work efficiently and affectivity to enhance the teaching activities in Iraq University.
Prediction of Link Weight of bitcoin Network by Leveraging the Community Structure
Authors: Rashid Atiya Hiba , Naji Nawaf Dr.Huda 
Published: November 2020

Abstract
In this work, the issue of predicting the edge weight in Bitcoin network has been addressed by leveraging community structure that involves members who trust with each other in their transactions. The proposed model consists of two main stages; the first one is the detection of trusted Bitcoin communities by implementing Newman- Girvan algorithm. In the context, the attributes of node have been modeling in different ways to get different structure of communities each time. Secondly, prediction the missing edge weight based on the neighbors of edge-source in community. In other words, the trust values that pointed to edge-target by neighbors are averaged to represent the prediction of missing edge weight. Practically, the model has been evaluated using two real-world datasets; Bitcoin-OTC and Bitcoin-Alpha datasets. The experimental results explicate the effectiveness of the proposed model comparable with other methods, where the minimization percentage for Bitcoin-OTC dataset is 4% and 18% for all and partial edges respectively. As for Bitcoin-Alpha dataset are 0% and 30% for all and partial edges respectively.
3D scenes semantic segmentation using deep learning based Survey
Authors: Y.Noori Amani , H. Shaker Shaimaa , abdulaali azeez Raghad 
Published: November 2020

Abstract
Semantic segmentation realization and understanding is a stringent task not just for computer vision but also in the researches of the sciences of earth, semantic segmentation decompose compound architectures in one elements, the most mutual object in a civil outside or inside senses must classified then reinforced with information meaning of all object, it’s a method for labeling and clustering point cloud automatically. Three dimensions natural scenes classification need a point cloud dataset to representation data format as input, many challenge appeared with working of 3d data like: little number, resolution and accurate of three Dimensional dataset . Deep learning now is the power and popular tool for data and image processing in computer vision, used for many applications like “image recognition”, “object detection”, “semantic segmentation”, In this research paper, provide survey a background for many techniques designed to 3 Dimensions point cloud semantic segmentation in different domains on many several available free datasets and also making a comparison between these methods.
Using Digital Image as a Cover of Information Hiding: Review Paper
Authors: saadi Abdullah Ahmed , Mohammed Hussein Qasim 
Published: November 2020

AbstractOne of the most important topics that concern many researchers is how to make information that has a high degree of confidentiality hidden and not accessible except by the people who have the authority to view it, images are one of the most important multimedia that can be used as a cover to include the data, because the image contains how much A huge amount of data that can include confidential information in it, as well as the image is one of the most multimedia that is sent and received thus that the process of messaging with pictures does not arouse suspicion, this research provided a detailed study of a group of articles that used the image as a cover in the inclusion of information Confidentiality, and focus was on the most important domains of strength in each article. Articles were studied from 2013 to 2020 that were published at the containers of Scopes, and Google Scholar.
Hausdorff Topological of Path in Graph
Authors: Jabor Ali A. , Omran Ahmed A. 
Published: November 2020

Abstract
Previous research has dealt with the topic of topological graph in several aspects and has studied the set of vertices or set of edges as a sub basis for topological space. The topic of domination has received the attention of many researchers in the recent period, because has many applications in the field of computers and networks. The main purpose of this paper is join between topological space and minimal dominating sets of a graph G, By using all minimal dominating sets (MDS) as open set of topology on V (G) . this paper discussed T
2 – MDS (hausdorff property) of path Pn
with n ≥ 4.
Some Approximation Properties of New Family of Baskakov-Type Operators
Authors: Sadiq Haneen J. 
Published: November 2020

Abstract
The aim of this paper is to establish a new family of Baskakov – type operators represented by summation type generalized Baskakov operators. Primarily, we discuss the properties of this sequences of L. P. O.. Further we view some approximation properties which lead us to establish a Voronovskaja theorem on this operators. Also, we study the rate of convergence when we show this new family preserve properties of modulus of continuity on a continuous function.
A Look at Sobolev Spaces on Graphs
Authors: Flaih Zainab , Samir Bhaya Eman 
Published: November 2020

Abstract
We study the Sobolev inqualities of real functions defined on graphs, when 0 < p < 1. These spaces are important than that the space of continuous functions.
In this paper we define the canonical embedding and study the existence of Sp
(G) which far from

l

p
m

when 0 < p < 1. Also we estimate the subspace of S

p
(G) isomorphic to

l

p
d

by Banach-Mazur distance of the corresponding dimension for 0 < p < 1.
Local Search Methods to Find Approximate Solution for The Sum of Two Criteria with Unequal Ready Times in Machine Scheduling Problem
Authors: Jabbar Khraibet Tahani , Khalid Jaber Waleed , Abed Dawood Lafta 
Published: November 2020

Abstract
This research concentrates on the study of SA / TS which is regarded as two of the approaches of modern artificial intelligence, to solve the problems of scheduling by single machine to minimize bi _ criteria

1
/

r
j

/

∑

j
=
1

n

w
j

(

1
−

e

−
r

c
j

)

+

T

max

. This problem settled up to 30000 jobs.
Retractable Modules Relative To A Submodule And Some Generalizations
Authors: Neamah Al-Aeashi Shukur , Hussein Al-Bakaa Fatimah 
Published: November 2020

AbstractA new generalizations of retractable modules relative to a submodule are introduced where a module ℳ is called retractable module relative to a submodule N of M if for all non-zero submodule K of ℳ such that contains N, there exists a non-zero homomorphism f∈Hom(ℳ, K). Some basic properties are studied and many relationships between these classes and other related concepts are presented and studied.
A Modification Fractional Homotopy Analysis Method for Solving Partial Differential Equations Arising in Mathematical Physics
Authors: Kamil Jassim Hassan , Gassab Mohammed Mayada , Ali Eaued Hossein 
Published: November 2020

AbstractIn this paper, we apply a new technique, namely fractional Sumudu homotopy analysis method (FSHAM) on fractional partial differential equations to obtain the analytical approximate solutions. The fractional derivative is described in the Caputo sense. This method is the combination of the Sumudu transform (ST) and homotopy analysis method (HAM). The method in general is easy to implement and yields good results. Illustrative examples are included to demonstrate the validity and applicability of the new technique.
Using the assumption G(q, r, s) = e

∫ y(q)dq + ∫x(r)dr + ∫ z(s)ds
for solving some kinds of linear third order P.D.Es. with homogenous terms
Authors: Naser Ketab Sattar 
Published: November 2020

Abstract
The preset paper aims at finding the complete solution of certain types of linear partial differential equations of third order with constant coefficients that have three independent variables (q, r, s) of the general form:

A
1

G

q
q
q

+

A
2

G

q
q
r

+

A
3

G

q
r
r

+

A
4

G

q
r
r

+

A
4

G

r
r
r

+

A
5

G

q
q
s

+

A
6

G

q
s
s

+

A
7

G

q
r
s

+

A
8

G

r
r
s

+

A
9

G

r
s
s

+

A

10

G

s
s
s

+

A

11

G

q
q

+

A

12

G

q
r

+

A

13

G

q
s

+

A

14

G

r
r

+

A

15

G

r
s

+

A

16

G

s
s

+

A

17

G
q

+

A

18

G
r

+

A

19

G
s

+

A

20

G
=
0

By using the assumption: G(q,r,s) = e

∫y(q)dq + ∫x(r)dr + z(s)ds
, the above equation, according to this assumption, will be transformed to the non-linear second order ordinary differential equation with three independent functions. Thus, they have the general form:

A
1

(

y
″

+
3
y

y
′

+

y
3

)
+

A
2

(

x

y
′

+
x

y
2

)

+

A
3

(

y

x
′

+
y

x
2

)

+

A
4

(

x
″

+
3
x

x
′

+

x
3

)

+

A
5

(

z

y
′

+
z

y
2

)

+

A
6

(

y

z
′

+
y

z
2

)

+

A
7

y
x
z
+

A
8

(

z

x
′

+
z

x
2

)

+

A
9

(

x

z
′

+
x

z
2

)

+

A

10

(

z
″

+
3
z

z
′

+

z
3

)

+

A

11

(

y
′

+

y
2

)

+

A

12

y
x

+

A

13

y
z
+

A

14

(

x
′

+

x
2

)

+

A

15

x
z
+

A

16

(

z
′

+

z
2

)

+

A

17

y
+

A

18

x
+

A

19

z

+

A

20

=
0

Note:- we used y instead of y(q) and χ instead of x(r) also ζ instead z(s).
Inverse Frame Domination in Graphs
Authors: Hamza Talib Sarai , A. Omran Ahmed , Rajihy Yasen 
Published: November 2020

Abstract
The generalization of the concept of inverse frame domination on graphs is the fundamental point of this work. It has been shown to present modern properties on inverse frame domination and some corresponding theorems related to delete, add edges or remove vertices. The relationship between the initial graph and a graph obtaining from the edges of the contraction was also discussed.
2-anti fuzzy domination in anti fuzzy graphs
Authors: J. Yousif Hayder , A. Omran Ahmed 
Published: November 2020

Abstract
The aim of this paper is to study the concepts of the concepts of 2- anti fuzzy dominating (2 – AFD) set and 2- anti fuzzy domination number (2 – AF domination number) of an anti-fuzzy graph (GAF
).We determine the 2- anti fuzzy domination number (2 – AFD number γ

2AF
) for some classes of an anti-fuzzy graphs (G

AF
) and obtain the bounds on (2 – AFD number) for the same. The relations between (2 – AF domination number), anti fuzzy domination (AF domination number) and vertex anti-fuzzy vertex covering number (α
0) are discussed and found some result.
Q-Smarandache Fuzzy Implicative Ideal of QSmarandache BH-Algebra
Authors: Hadi Abbass Husein , Mohsin Luhaib Qasim 
Published: November 2020

Abstract
In this paper, The notions of Q-Smarandache fuzzy implicative ideal and Q-Smarandache fuzzy sub implicative ideal of a Q-Smarandache BH-Algebra introduced, examples are given, and related properties investigated the relationships among these notions and other types of Q-Smarandache fuzzy ideal of a Q-Smarandache BH-Algebra are Studies.
Using of Genetic Algorithm to Evaluate Reliability Allocation and Optimization of Complex Network
Authors: Abdullah Ghazi , Haddi Hassan Zahir Abdul 
Published: November 2020

Abstract
In this paper the allocation of reliability and optimization has been calculated for each component of the complex system. Use (genetic algorithm) to solve the problem of allocation and to optimize system reliability. Also discussed are the three expense functions (exponential behavior with feasibility factor model, exponential behavior model and logarithmic model). The reliability importance of each component of the system was calculated after solving the allocation problem. The aim of this paper was to compare the results of the three cost functions by using GA in terms of reliability allocation and optimization, accurate reliability, reliability importance, and then whatever is more efficient than another.
A Developed Approach to Estimate the Reliability of Atomium Bridge
Authors: A. Abdul-Razaq Abeer , Talib Hasson Saad 
Published: November 2020

Abstract
In this paper special attention was focused on a system that cyclic paths and one terminal, this paper produces a new technique to evaluate the reliability system and how to make a special kind of equations to arrive to the reliability of each part of the system network.
Comparison of Box-Jenkins models predicting Iraq’s population growth rate
Authors: Harbi Odah Dr. Meshal 
Published: November 2020

Abstract
The prediction of the urban population growth rate it gives estimate the expected change in the rate of growth in the future Based on socio-economic development and geography of the population, The use of time series analysis is one of the most important statistical methods used in the study and analysis of annual, monthly and daily data To prediction the values of future random phenomena based on what happened in the past which helps in making future plans for economic development. The goal of most of the statistical population studies is to provide an approximate forecast future population. In this paper, the Box-Jenkins models were compared to predict the rate of population growth in urban areas until the year (2033) based on the criterion of the mean absolute percentage error (MAPE) to choose the best prediction model.