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Identity and access management (IAM) system usually consist of predefined tasks as an information security system. Themain task is the authentication, since it is responsible for user identity proving for service providers that corporate with (IAM).This paper provides a review on intelligent authentication research applicable to IAM systems. These researches areevaluated according to the proposal of intelligent authentication key factors. Depending on this evaluation it could not be foundresearch implement an authentication that satisfies all these key factors.

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.

This paper involves a determination of paracetamol using less environment harmful reagent; the hydroxy analog of the pharmaceutical naproxen replaced a chemical reagent in which it is used as a coupling agent for the diazotized p-aminophenol (the hydrolysis product of paracetamol), the paper offers a determination of an analgesic paracetamol in the presence of high content of another analgesic. Paracetamol azo-dye exhibits maximum absorption at 500 nm. Beer's law is obeyed over the concentration range from 10 to 650 µg/20ml, (i.e. 0.5-32.5 ppm) with a good sensitivity (molar absorptivity 1.2x104 l.mol-1.cm-1), good precision (RSD better than ±0.275%) and high accuracy (relative error less than + 0.77%), Sandell's sensitivity index is 0.0124µg.cm-2, the limit of detection (LOD) is 0.0030 µg/ml and the limit of quantitation (LOQ) is 0.0101 µg/ml. The method has been successfully applied for determination for paracetamol in dosage forms and its already applicable for the determination of paracetamol in presence of naproxen.

The importance of big data implementations is increased due to large amount of gathered data via the online gates. The businesses and organizations would benefit from the big data analysis i.e. analyze the political, market, and social interests of the people. The Internet of Things (IoT) presents many facilities that support the big data transfer between various Internet objects. The integration between the big data and IoT offer a lot of implementations in the daily life like GPS, Satellites, and airplanes tracking. There are many challenges face the integration between big data transfer and IoT technology. The main challenges are the transfer architecture, transfer protocols, and the transfer security. The main aim of this paper is to review the useful architecture of IoT for the purpose of big data processing with the consideration of the various requirements such as the transfer protocol. This paper also reviews other important issues such as the security requirements and the multiple IoT applications. In addition, the future directions of the IoT-Big data are explained in this paper.

Currently, there are many approaches for image transformations that are developed to cover the new technology in the huge amount of data treatment. In this paper, a study on Curvelet transformation coefficients was performed based on the aerial image to apply segmentation. This paper applies a lot of modifications on cut off frequencies on the filters, which is used to decompose the image on curvelet transformation. Two approaches are proposed and tested to look for the best segmentation result; the first one is based on designing filters manually, while the second evaluates the filter coefficients depending on the selected shape of the filters. The first technique gives acceptable segmentation and the second reaches the optimal result. One of the most important results is that the cut of frequency has a high effect on the segmentation; in addition, choosing filter parameters depended on the coefficients dimension of the curvelet transformation. Finally, the results show that the first approach underperformed the second one.

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.

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

In lately years, data streaming is become more important day by day, considering technologies employed to servethat manner and share number of terminals within the system either direct or indirect interacting with them.Smart devices now play active role in the data streaming environment as well as fog and cloud compatibility. It is affectingthe data collectivity and appears clearly with the new technologies provided and the increase for the number of theusers of such systems. This is due to the number of the users and resources available system start to employ the computationalpower to the fog for moving the computational power to the network edge. It is adopted to connect system that streamed dataas an object. Those inter-connected objects are expected to be producing more significant data streams, which are produced atunique rates, in some cases for being analyzed nearly in real time. In the presented paper a survey of data streaming systemstechnologies is introduced. It clarified the main notions behind big data stream concepts as well as fog computing. From thepresented study, the industrial and research communities are capable of gaining information about requirements for creatingFog computing environment with a clearer view about managing resources in the Fog.The main objective of this paper is to provide short brief and information about Data Streaming in Fog ComputingEnvironment with explaining the major research field within this meaning.

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.

A class of modification is proposed for calculating a score for each Player/team in Unbalanced Incomplete paired Comparisons Sports Tournaments. Many papers dealing with Balanced Incomplete Paired Comparison Sports Tournaments with at most one comparison per pair have appeared since 1950. However, little has been written about unbalanced situations in which the player /the team (object) ( j ) plays unequal number of games against the player/the team( m ) in a tournament, and the results of all games can be summarized in a Win-Lose matrix Y = { Yjm } , where Yjm = 1,0,1/2, respectively, according to as the player or the team ( j ) wins, losses or draws against the player or the team (m ). Published papers by Ramanujacharyulu (1964), Cowden, D.J. (1975), and David, H. A.(1988) have concentrated on the problem of converting the results of unbalanced incomplete paired comparison tournaments into rank with little consideration of the main relative ability on each player or team. We suggest (modification) another way of quantifying the outcomes of the games/tournaments, in particular, ratings on a scales, 0 to 5, 1 to 10 .ect. It is important to consider not only the vector Vj(d) or the vectors Sj, in scoring and ranking the k teams in such tournaments, but also the vector Zj, where Zj = Sj + SjRj, to take into account the ratio of the relative ability of each team ( Rj ). The proposed modification helps to introduce these methods for use in comparisons/games (tournaments), where the player/team are quantified on a special scale. e.g. 0-5, 1-10, ..etc. We conclude the following:- The scores stabilized to three decimal places at iteration 2 in Cowden’s method Vj(d) .see table(1.4). The scores stabilized to three decimal places at iteration 2 in David’s method Sj , and it’s modification Zj. The proposed modification (Zj) has the advantage of removing ties from David’s method (Sj), and hence it is the best method.

License Plate Recognition (LPR) system becomes animportant research issue in recent years due to its importance to wideranges of commercial applications. The first and the most importantstage for any LPR system is the localization of the number platewithin the vehicle image. This paper presents a methodology for Iraqicars number plates extraction from the vehicle image using twomethods, the first one is morphological operations and the secondmethod is edge detection. The main idea is to use these two differentmethods in such away so that the number plate of the vehicle can beextracted precisely. These algorithms can quickly and correctly detectand extract the number plate from the vehicle image although therewas a little noise in the image. This paper also makes a comparisonbetween the two methods of extraction in results. The software thatused to build the systems is MATLAB R2014a

In this paper many algorithmswereapplied to" zoom –out" the images, like the traditional algorithm (Linear Averaging) algorithm, then this algorithm was developed to a proposed algorithm (Block Averaging) to be the new one in this paper. another algorithm is obtained from another application which is involved as an enhancement smoothing algorithms and will be used as a (zooming-out) scheme, this algorithm is the (Median) algorithm. The obtained results of these algorithms were compared together to sign the better one. The MATLAB language is used to apply the algorithms. .

The aim of this paper is to trace the contemporary perceptions/definitions of the translator and translation in Turkey where the translation profession is not a legally regulated profession. (In)visibility of the translator and the scope of his/her expertise are widely debated issues among both the scholars/students of translation and the various players in the world of translation. Although translation is no longer being defined as a mere linguistic activity, reductionist views of translation that equate translation to 'know'ing a foreign language still continues to prevail. What accompanies the said reductionist view is the claim that a translator can not translate 'all the texts' in different fields of expertise, at least not as successfully as the 'real' experts of the field who also know a foreign language such as engineer-translators or lawyer-translators who know English. However, recent developments concerning legal translation in plurilingual settings evidence a completely different understanding of translation and the identity/expertise of the translator. In such settings, translators work together with the drafters of the legal texts and are responsible for the source legal texts as well as the target ones, broadening the scope of the 'expertise' of the translator in an unprecedented way. In the light of the implications of the said transformation of the identity of the legal translator, this paper argues that the identity/definition of the translator/translation needs to be reconsidered and the results should be reflected onto the translator training programs with the aim of helping students of translation (re)define their identity as real 'experts' of the translation field and contributing to the transformation of the perception of translation and the translator.

In this paper, a new proposed method is developed, this method contains two algorithms, one for human iris recognition, the other is for extracting the features of the recognized iris. Many studies tried to extract the iris from images, most of those studies succeeded but after using very complex processing and filtering operations in addition to transforming the image to other domains (such as frequency domain) to achieve the required operations. The proposed method deduct those complexities operations to a minimum and requires only wavelet transform in a small part of the second algorithm, all other operations will be applied directly to the spatial domain. Experimental results shows the efficiency of the method as its being applied to the images of the Chinese Academy of Sciences – Institute of Automation “CASIA” iris database which contains a lot of deformations. Finally, Matlab R2010a (Ver. 7.10.0) was used to implement the algorithms presented in this paper because it facilitates handling images, arrays, and filters.

The didactic bags which are programs designed to replace the teacher in a certain scientific field, are the modernist didactic means which proved great activity in the didactic process and due to the importance of the images processing field of computers, so It has been constructed in this paper on designing of didactic bag in the bases of the images processing field which is considered as one of the classification of computer imaging. The research deals with the images processing in that the idioms. It deals the most famous idioms of images processing. It also treats of some of the images folders shapes. It deals with parts of images processing in detail as well as giving instance to illustrate each of these parts. It deals with the associating process with the parts of the images processing in that digital filtration and mathematical rolling, besides it deals with the special commands in the images processing in some programming languages as Matlab language, c++ language and visual basic language with giving some instances. The paper also contains a show for some internet sites in order to give the opportunity to the user to increase his knowledge and expertise if he wishes to sight the internet sites.

In this paper an image is hidden in another image using one of the hiding algorithms (Least Significant Bit) to produce the stego-cover image which used as an input with the cover to Radial basis function Network to produce the weights. Cover is delivered once to the recipient who can use it for unlimited number of messages. The weights are delivered to the recipient for each hidden message as a key. The recipient uses the cover with the weights to unhide the message. So that this method include two levels of security. The first one is hiding the message in the cover to produce stego-cover image. The second one is ciphering the embedded image using RBF Neural Network. This Network is considered as a target and the input to the Neural Network is the cover image. Then the weights, which represent the encrypted information are reconstructed. The recipient can use RBF Network to unhide the message by having the stego-cover image then the message. Matlab R2008a was used in this paper.

In this paper many algorithmswere applied to" zoom –in" the images, like traditional algorithms which is used (Linear Averaging) algorithm, (Convolution) algorithm and the proposed algorithms to be the new algorithms in this paper. These algorithms are obtained from another application which involves in Enhancement Smoothing Algorithms and will be used as a (zooming-in) color images algorithms which are include (Median) Algorithm and (Max & Min) Algorithm and sometimes called (Conservative Smoothing Algorithm). The obtained results of these algorithms were compared together. The MATLAB language is used to apply the algorithms.

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.

Patients at healthcare facilities require a long-term continuous healthcare monitoring system to keep track of their vital signs. Because it deals with human life, this system must be safe, trustworthy, and ensure that it does not interfere with available radio frequencies or sensitive electronic devices such as MRI (magnetic resonance imaging). This paper introduces a patient monitoring system in intensive care that used Li-Fi technology, designed to help enhance patient care and boost doctor’s clinical results. This robust approach timely collects patient data and integrates securely within the hospital IT framework feeding information to physicians, allowing them to make informed clinical decisions. The system used real-time software which displays the data from different locations for assessment. It was successfully tested in the laboratory. Some measurements are discussed, which compare the received pulses to the modules line of sight (LOS) output channel to correlate the transmitted channels. In this work, experimental analysis and measurements are performed to check the efficiency of the proposed concept.

Network safety has become an important issue in recent years. Encryption has been developed as a solution and plays an important role in the security of information systems. Many methods are required to secure the shared data. The advanced internet, networking firms, health information and the cloud applications have significantly increased our data every minute. The current work focuses on cryptography to provide the protection for sensitive data that exchanged between personal users, companies, organizations, or in the cloud applications and others during the transfer of data across the network. Firstly, Data sent from sender to network receiver must be encrypted using the cryptographic algorithm. Secondly, the recipient shows the original data using the decryption technique. This paper presents three encrypting algorithms such as AES, RSA and hybrid algorithms, and their efficiency is compared based on the analysis of the time. Results of the experiments show that the hybrid algorithm is better in term of security.

Many papers have been published about manipulating computer viruses; instructions that impact a computer system and after a period of incubation and reproducion, activate and demonstrate their presence. mest Viruses were designed to attack microcomputers, sincce microcomputers are widely used nowadays, and have simple operating systems which result in lack of quality of their security systern. Connecting computers with networks and using copies of programs from unreliable sources such as bullet in board systems will increase the :of viral contact and the spread of viruses. Data Encryption disguises data flowing through a network so that it is unintelligible to any one monitor the data, Encryption techniques can also be used to detect file modification which may caused either by unithorized users or by viruses. This paper concern in viruses atracking users on system files (.exe and com) in microcomputer sytems, where viruses Types, how they work, and anti-virus streiagies are going o scussed. Finally, a dccction stralegy depending on Encryption techniques built the operating sysiems Suggested to improve PCs Security and preventing unauthorized users from inserting into programas commands that will cause system corruption.

This research paper includes designing and implementing of an Electronic system for managing theses of College of Computer Science and Mathematics, University of Mosul, using replication, C # language and MS SQL Server 2008 databases to be a stable work basis that can be relied upon in the departments’ work as it facilitates the higher administrative bodies in the departments and the deanship Obtaining the required results quickly and accurately, which facilitates and contributes to making the right decisions at the appropriate time and required with the ease of preparing special reports for each student, lecturer and thesis and printing them which it will help the departments head and the scientific committee to complete them if requested, as well as provide various statistics, and to improve administrative efficiency for thesis, the problem of losing thesis data and preserving it from human and natural disasters has been overcome by applying the principle of replication.

A chatbot is a computer program which is designed to interact with users and answer questions. Nowadays, chatbots are one of the most common systems that are used in many fields and by different companies to achieve different tasks. Cloud computing is gaining increasing interest. A myriad of fields and applications have been developed based on cloud computing. In this paper, a college chatbot was developed and implemented to assist students to interact with their college and ask questions related to faculty, activities, exams, admission, amongst other tasks. Text similarity algorithms were adopted to achieve the proposed system. More specifically, cosine similarity and jaccard similarity algorithms were used to find the closest question in the dataset. Firebase real-time database, which is one of the Google cloud services, was used as a connector channel between users and the chatbot server. Experiments were conducted to evaluate the performance of cosine similarity and jaccard similarity methods, and to compare the results of both. In addition, real-time database was also evaluated as a chatbot connecter channel.

Due to the great electronic development, which reinforced the need to define people's identities, different methods, and databases to identification people's identities have emerged. In this paper, we compare the results of two texture analysis methods: Local Binary Pattern (LBP) and Local Ternary Pattern (LTP). The comparison based on comparing the extracting facial texture features of 40 and 401 subjects taken from ORL and UFI databases respectively. As well, the comparison has taken in the account using three distance measurements such as; Manhattan Distance (MD), Euclidean Distance (ED), and Cosine Distance (CD). Where the maximum accuracy of the LBP method (99.23%) is obtained with a Manhattan and ORL database, while the LTP method attained (98.76%) using the same distance and database. While, the facial database of UFI shows low quality, which is satisfied 75.98% and 73.82% recognition rates using LBP and LTP respectively with Manhattan distance.

Nowadays, the field of Internet of Things (IoT) has become a new trend and one of the most attractive areas of research. It has a wide range of applications; starting from smart devices to developing smart cities. The main issue in this kind of applications is the limitation in network resources (e.g., energy, memory, connectivity, etc.). Most of the works in the literature deal with this issue in a traditional way. For instance, developing routing protocols that find the optimal path for data forwarding. This paper looks to this issue from a different angle. In this work, we aim at testing different mobility patterns and then investigate their impact of the consumption of network resources under particular distributions and data routing protocols. The aspect we aim to investigate and measure is the amount of data exchanged, which in turn affects the power and the memory consumption of a network. We also measure two more aspects; performance stability, and data coverage area. The results show that mobility models play a significant role in the overall network performance.

This paper explores the stages of speaking skill's online lectures using the Zoom Cloud Meeting media as well as the advantages and disadvantages of the Zoom Cloud Meeting media. This study used a descriptive qualitative approach with three data collection techniques, namely observation, interviews, and documentation. The results showed that there were several stages used by lecturers in the implementation of speaking skill lectures using Zoom Cloud Meeting media, namely: (1) Pre-Lecture, (2), Lecture Implementation, (3) and Class Evaluation. There are several features of the Zoom Cloud Meeting media used by lecturers in the implementation of speaking skill lectures such as Schedule, mute & unmute, record, chat, and whiteboards. Researchers also found several advantages regarding the implementation of speaking skill lectures using Zoom Cloud Meeting media such as flexibility in the lecture process, increasing discipline for lecturers and students, and several additional features that can support the smooth implementation of lectures. However, the implementation of lectures using this media is also inseparable from shortcomings such as a poor internet network and limited duration of the free Zoom Cloud Meeting media which can only be used for 40 minutes. From the results of this study, it is hoped that it can provide alternative solutions for lecturers in dealing with online lectures in the midst of the COVID-19 pandemic.

Data stream clustering refers to the process of grouping continuously arriving new data chunks into continuously changing groups to enable dynamic analysis of segmentation patterns. However, the main attention of research on clustering methods till now has been concerned with alteration of the methods updated for static datasets and changes of the available modified methods. Such methods presented only one type of final output clusters, i.e. convex or non-convex shape clusters. This paper presents a novel two-phase parallel hybrid clustering (HPPD) algorithm that identify convex and non-convex groups in online stage and mixed groups in offline stage from data stream. In this work, we first receive the data stream and apply pre-processing step to identify convex and non-convex clusters. Secondly, apply modified EINCKM to present online output convex clusters and modified EDDS to present online output non-convex clusters in parallel scheme. Thirdly, apply adaptive merging strategy in offline stage to give last composed output groups. The method is assessed on a synthetic dataset. The output results of the experiments have authenticate the activeness and effectiveness of the method.

In this paper, has been proposed Algorithm for standard JPEG2000 part one for image compression. The proposed Algorithm was executed by using MATLAB7.11 environment, applied these algorithm on the gray and color images for type of the images natural, medical, Graphics images and remote sensing. Dependence on the Peak Signal-to-Noise Ratio (PSNR) for comparing the result of the proposed Algorithm by using the Daubechies filters 5/3 tap filter and 9/7 tap filter Biothogonal , Another comparison is held concerning the obtained results of the algorithm of ModJPEG and Color-SPECK. Proved the processing results Efficiency performance of proposed Algorithm.

Bank loans play a crucial role in the development of banks investment business. Nowadays, there are many risk-related issues associated with bank loans. With the advent of computerization systems, banks have become able to register borrowers' data according their criteria. In fact, there is a tremendous amount of borrowers’ data, which makes the process of load management a challenging task. Many studies have utilized data mining algorithms for the purpose of loans classification in terms of repayment or when the loans are not based on customers’ financial history. This kind of algorithms can help banks in making grant decisions for their customers. In this paper, the performance of machine learning algorithms has been compared for the purpose of classifying bank loan risks using the standard criteria and then choosing (Multilayer Perceptron) as it has given best accuracy compared to RandomForest, BayesNet, NaiveBayes and DTJ48 algorithms.

The aim of this paper is to reach the best balance point between the maximum reliability and minimum lost cost when injecting Distributed Generation (DG). The new Al-Kadimeya substation in Al-Kadimeya sector in Iraq – Baghdad was chosen for this research, because there is a group of four diesel generator injected in it is mesh. These DGs suffers from stop working and interruptions in the supply of energy, which causes its failure to do its task of supporting the national grid in electrical power. This substation has fifteen different feeders. Five diverse feeders were selected to inject DGs in it. The injection was in several locations on the selected five feeders sequentially. Zone branch methodology applied in analysis these feeders and the required calculations were carried out until the best site with the lowest failure rates was reached to inject these generators, which is feeder 2. The failure rates of the five feeders were reduced by 151 times, about 14%. Outages duration were reduced by five h/y, approximately 3.67%.The lost power costs for all previous test sites of injecting distributed generation were then calculated too. Then the site with the highest lost power (i.e. the one of the highest lost cost) was selected to inject the generators to it which was feeder 2 also, where the expected lost costs due to interruptions were reduced by 510,000 USD /y, about 16.4%. Results show that feeder 2 represents the best location for injection of the DGs instead of the current location on feeder 4.

This paper describes the use of Scribe Video as a Media in Learning Arabic to Improve Student Learning Motivation. The problem of education and teaching is a fairly complex problem where there are many factors that influence it. One of these factors is the teacher. The teacher is a component of teaching that plays an important and primary role, because the success of the learning process is largely determined by the teacher's factor. The teacher's task is to convey the subject matter to students through communication interactions in the learning process that they do. The success of the teacher in delivering the material is very dependent on the smooth interaction between the teacher and the students. This study uses development research methods in education or in English development research, a process in developing and validating educational products. The purpose of this research is to develop Arabic learning media using software sparkol (video scribe) in increasing student learning motivation. This research is a research and development focusing on software sparkol (video scribe). Videoscribe is a software (software) for automatically creating whiteboard animation (whiteboard animation). Videoscribe was launched in 2012 by sparkol company United Kingdom (UK) in the UK. Videoscribe is developed by Adobe Flash and Flash Video. Videoscribe is a form of video media with a blackboard concept that uses hand drawings and as if it were drawing or writing on the board. The concept of videoscribe is usually used as a video presentation, promotion, learning, and so on.

Inn then last two decades the Content Based Image Retrieval (CBIR) considered as one of the topic of interest for theresearchers. It depending one analysis of the image’s visual content which can be done by extracting the color, texture and shapefeatures. Therefore, feature extraction is one of the important steps in CBIR system for representing the image completely. Color featureis the most widely used and more reliable feature among the image visual features. This paper reviews different methods, namely LocalColor Histogram, Color Correlogram, Row sum and Column sum and Colors Coherences Vectors were used to extract colors featurestaking in consideration the spatial information of the image.

Greenberg (1972) in a study based on a sample of about 100 languages with numeral classifiers, attempted to determine the conditions under which anon- classifier language might become a classifier language. Later Hale and Shresthachrya (1973) made their attempts to seek whether Newari is considered as a classifier language or not. The purpose of this study is to analyze the Kurdish classifier system based on the Greenberg (1972) whether Kurdish is a classifier language or not, the paper also compares classifier constructions in English and Kurdish, with the aim of addressing the research questions: what linguistic devices are used in Kurdish and English for classification? How different or similar are classifiers in Kurdish and English as non-classifier language. Classifiers in Kurdish have not been studied extensively and there are not any references available on classifiers of Kurdish in English. Therefore, by considering the classifier system of Kurdish, this study makes attempt to provide an introductory source of analytical research of grammar in Kurdish.

Deep learning of multi-layer computational models allowed processing to recognize data representation at multiple levels of abstraction. These techniques have greatly improved the latest ear recognition technology. PNN is a type of radiative basis for classification problems and is based on the Bayes decision-making base, which reduces the expected error of classification. In this paper, strong features of images are used to give a good result, therefore, SIFT method using these features after adding improvements and developments. This method was one of the powerful algorithms in matching that needed to find energy pixels. This method gives stronger feature on features and gives a large number of a strong pixel, which is considered a center and neglected the remainder of it in our work. Each pixel of which is constant for image translation, scaling, rotation, and embedded lighting changes in lighting or 3D projection. Therefore, the interpretation is developed by using a hierarchical cluster method; to assign a set of properties (find the approximation between pixels) were classified into one.

Characterizing of visual objects is an important role in pattern recognition that can be performed through shape analysis. Several approaches have been introduced to extract relevant information of a shape. The complexity of the shape is the most widely used approach for this purpose where fractal dimension and generalized fractal dimension are methodologies used to estimate the complexity of the shapes. The box counting dimension is one of the methods that used to estimate fractal dimension. It is estimated basically to describe the self-similarity in objects. A lot of objects have the self-similarity; fingerprint is one of those objects where the generalized box counting dimension is used for recognizing of the fingerprints to be utilized for authentication process. A new fractal dimension method is proposed in this paper. It is verified by the experiment on a set of natural texture images to show its efficiency and accuracy, and a satisfactory result is found. It also offers promising performance when it is applied for fingerprint recognition.

A lot of institutions depends at present on the systems database operations and their daily activities, thus providing a means for the maintenance of permanent data can refer to it at any time, as well as to search and to modify the data easily. in this paper to determine the security challenges in the databases, and requirements necessary to address those challenges in the data value to provide security base, and to determine the security rules and know the weaknesses that can be exploited any information in a manner not allowed, when he must protect the database to make sure of the following purposes: confidentiality, integrity and continuity. One of the solutions used in this research to protect databases, and encryption of sensitive data, and adjust the system databases, and updates the database systems and we review some of the ways to address these challenges in the security databases.

In this paper, an alarm system for four types of emergency states (explosion, car accident, earthquake and fire) is developed. This system divided in to two parts: transmitted part (Arduino, sensors, GSM, GPS), and emergency part (center site, sub center sites). Center site is included (Android phone, Server), Sub center sites (helping centers) represented the mobile phones of competent authorities like police center or hospital. The alerting in this system as a SMS message is sent by GSM. The system used Haversine formula to determine the nearest sub center from emergency state that receives the SMS alarm message from transmitted part. Also the path is tracked using Google map application.

The purpose of this paper is to determine the technique of examination and processing of assessment results. This research uses a type of library research, namely research that uses various literature sources such as books and journal articles to serve as writing guidelines. This article's results indicate that there are steps that must be carried out in the assessment, namely when examining and processing the assessment results. In the stage of checking the assessment results, correcting the students' answers carefully and thoroughly according to the existing scoring guidelines. The raw scores obtained so that they become more meaningful and must be interpreted based on specific and relevant assessment references and needs, namely by benchmarking reference assessments ( PAP) and norm-referenced assessment (PAN). For example, to determine whether students' scores have met the passing grade predetermined, then use a benchmark reference assessment. Meanwhile, to determine the comparison of students' scores, it uses the norm reference assessment.

Basically, there are many moslems who memorize Qur'an in sequence from beginning to end. This methods is called conventional methods that need left brain ability. On the other hand, the method of memorizing the Qur'an with the right brain ability the contemporary method, this method has lots of results such as verse, translation, memorization from front to back or vice versa and random. This paper aims to find out the method thas use to memorize the Qur'an by right brain. The conclusion from this study is in memorizing Qur'an there is (Brain Based Learning). This method is highly optimize the right brain activity by applying 5 methods as follows: 1) method of story. 2) method of replacement. 3) method of location. 4) method of number. 5) method of sentence.

The segmentation performance is topic to suitable initialization and best configuration of supervisory parameters. In medical image segmentation, the segmentation is very important when the diagnosing becomes very hard in medical images which are not properly illuminated. This paper proposes segmentation of brain tumour image of MRI images based on spatial fuzzy clustering and level set algorithm. After performance evaluation of the proposed algorithm was carried on brain tumour images, the results showed confirm its effectiveness for medical image segmentation, where the brain tumour is detected properly.

– Content-based search provides an important tool for users to consume the ever-growing digital media repositories. However, since communication between digital products takes place in a public network, the necessity of security for digital images becomes vital. Hence, the design of secure content-based image retrieval system is becoming an increasingly demanding task as never before. This paper, presents a mechanism that addresses the secure CBIR as a novel improvement and application for the image retrieval. The proposed system consists of six phases briefly described as follows: first, feature extraction phase, which produces the low-level quantitative description of the image (color and texture) that allows the computation of similarity measures, the definition of the ordering of the images, and the indexing of the search processes. Second, indexing for search process phase, hash table and bloom filter were employed for classification . Third, feature encryption phase, where content protection is performed using a method developed by us (including Chaotic Logistic Map) . Fourth, image encryption phase, as security mechanism for CBIR, we combine two research fields in computer science, CBIR and image cryptography, which grow up to meet the trends of security and speed in current computer sciences, chaos and stream cipher systems were applied as an image encryption system. Fifth, the retrieval phase, which provides a subset of images answering the query based on the similarity between images computed over the feature vector extracted from each image. Finally, Relevance feedback phase , a technique that attempts to capture the user’s needs through iterative feedback. Although the system proved its efficiency in search performance (with 88% of average precision), security strength, and computational complexity, it does not mean the optimal system is designed, since some weakness points still can be found that are suggested to be improved as a future work.

The process of classification and recognition of the digits is very important and accurate issue, it should depend on a strong, adequate rule, because there are differences in the representation of the digits for various type of font, rather than to get homogeneous classification for group of digits to show the form or the constant shape for the digit from groups of font , where to be one shape represents each group of the shapes and sizes. This paper proposed a new method for recognition images of Arabic digits with various types and size of font which captured by various kind of camera and various resolution depending on the characteristics of each digit which extracted from study of ten types of font with various size for each type. The characteristic of all shapes and sizes extracted for each digit. Then made a constant model for each digit to be compare with the digit image in any size or font type to recognize the digit in the image. A database of ten templates (one for each digit) built, and these templates are basic and general to recognize the Arabic digits with various font and size. The new method applied for recognition of Arabic digits in the images of license plate of the passenger cars. the recognition percentage was 98%.

This paper propose a method for security threw hiding the image inside the speech signal by replacing the high frequencycomponents of the speech signal with the data of the image where the high frequency speech components are separated and analyzed usingthe Wavelet Packet Transform (WPT) where the new signal will be remixed to create a new speech signal with an embedded image. The algorithm is implemented on MATLAB 15 and is designed to achieve best image hiding where the reconstruction rate was more than 94% while trying to maintain the same size of the speech signal to overcome the need for a powerful channel to handle the task. Best results were achieved with higher speech resolution (higher number of bits per sample) and longer periods (higher number of samples in the media file).

This paper investigates the field of Video image analysis depending on texture for detecting a goal and tracing its movement in a video series. Analysing images depending on texture is better than depending on colour or shape , for the goal sometimes depends on different features . The aim of this study is to propose a method for tracing a goal within a video series after detecting it in each video frame. This study exhibits one of the techniques of extracting the image features depending on the signal frequency through using Gabor filter and in different trends for each frame. Then the histogram is taken for each frame and the frame given the best description for the goal is selected , in which case the threshold is depended . Then it is transformed into the binary form of the video frame ,to decrease time consumed short in detecting the object target . The algorithm is applied to part of the video frame . The location of the object target is determined through calculating the centre for part of the frame and the operation is applied to the series of the frames of the video film . Two films have been adopted as a research sample ,The first is a person„s movement by the traffic lights in al-Nabi Yunus area and the other are the students movement at the university of Mosul in the College of Education.

Blood cells are composed of erythrocytes (Red Blood Cells (RBCs)), the shape of RBC changes when the body suffers from different diseases such as Anemia. Classification of such diseases helps the medical technician to decide the type of Anemia in Laboratory analyzes in the hospitals. This paper proposed an automatic classification algorithm, which discriminates the different types of Anemia using Principal Component Analysis (PCA) algorithm and Decision tree. The proposed algorithm consists of four steps, at the first step preprocessing steps are applied on the RBC image, these RBC images then segmented in the second step, features are extracted using moment invariant in third step, this features are considered input to PCA so as to produced features vectors, at a final step features vector are inputted to Decision Tree to classify RBC image. Best classifications rates are (92%) obtained when using PCA algorithm compared with (74.1 %) which are obtained without applying PCA algorithm.

Wireless sensor network WSN consists of small sensor nodes with limited resources, which are sensing, gathering and transmitting data to base station. Sensors of various types are deployed ubiquitously and widely in varied environments for instance, wildlife reserves, battlefields, mobile networks and office building. Sensor nodes are having restricted and non replenishable power resources and this is regarded as one of the main of their critical limits. All applied techniques and protocols on sensor nodes must take into consideration their power limitation. Data aggregation techniques are used by sensor nodes in order to minimize the power consumption by organizing the communication among sensor nodes and eliminating the redundant of sensed data. This paper proposed lightweight modification on data aggregation technique named Energy Aware Distributed Aggregation Tree EADAT. The main principle of this development is using the available information in sensor nodes to pass the role of parent node among sensor nodes in each cluster. The process of passing parent node role is based on nominating the sensor nodes which have higher power on regular bases. A model based on tree network architecture is designed for validation purpose and is used with NS2 simulator to test the proposed development. EADAT and EADAT with proposed development are applied on the designed model and the results were promising

Cloud computing-based technology has become in many modern organizations concerned with educationinstitutions. It will likely have a significant impact on the educational environment in the future. Universities takeadvantage of available cloud applications offered by service providers and enable their own users/students to performbusiness and academic tasks.In this paper, reviewing what the cloud computing infrastructure will provide, a literature review providing thecontext from the infrastructure, application and services aspect of cloud computing, it was also look for the answers of itsbenefits to higher education institutions and different educational uses. Also introduce cloud computing to educatorsand help them to gain a better understanding of the conception of cloud technology and its impact on teaching and learning ininstitutions.

The solid oxide fuel cell (SOFC) is considered extremely suitable for electrical power plant application. Both high temperature (HT) and intermediate temperature (IT) SOFC performances are investigated using models which are built in Aspen customer modeller. Moreover, this paper introduces a new simulation software, called Al-Nour V.1.0-2012 software application. The interface of Al-Nour V.1.0-2012 software was mainly implemented based on the educational theory of User’s Split Attention, that is; the entire software works with only one screen for all operations without any scrolling (user-friendly interface). This application reflects the fact that Al-Nour software does not require the user to have any previous training. The performance of HT-SOFC and IT-SOFC models is evaluated and compared using both software applications . The simulation results show that, the cell voltage value increases by raising the operating pressure, operating temperature, and hydrogen partial pressure. The electrical power output value from the SOFC is increased simultaneously by increasing the current density . Furthermore, the IT-SOFC has a higher cell voltage than the HT-SOFC.

In general, path-planning problem is one of most important task in the field of robotics. This paper describes the path-planning problem of mobile robot based on various metaheuristic algorithms. The suitable collision free path of a robot must satisfies certain optimization criteria such as feasibility, minimum path length, safety and smoothness and so on. In this research, various three approaches namely, PSO, Firefly and proposed hybrid FFCPSO are applied in static, known environment to solve the global path-planning problem in three cases. The first case used single mobile robot, the second case used three independent mobile robots and the third case applied three follow up mobile robot. Simulation results, which carried out using MATLAB 2014 environment, show the validity of the kinematic model for Nonholonomic mobile robot and demonstration that the proposed algorithm perform better than original PSO and FF algorithms under the same environmental constraints by providing the smoothness velocity and shortest path for each mobile robot.