Search

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.

English is getting more crucial to be mastered since its important part in the world nowadays. It is not only as a means of communication but also a means transferring knowledge, news, and technology around the world. There are four basic skills in English such as listening, speaking, reading, and writing, every students must have problem in learning and mastering those skill. But writing is the main issue to be discussed in this article. In writing, some of the writer’s students feel difficult to determine the topic when they want to write, they are hardly to complete a writing paper because they run out of idea. In this case the students need to absorb some information to understand a word, including how to combine a word with the other words. Therefore the teacher should have a strategy to get the students understanding and overcome their problems.Teaching is about just how to encourage the learners to achieve their goals and other times it requires that we actually facilitate resources and foster experiences so students can learn, continue learning and love the process. It is an art of the teacher to know how to make the students able to create knowledge of their own. Brainstorming is one of the teaching techniques in writing that can encourage the students to think about the topic as many as possible. This technique is help the students to enrich their vocabularies then create an idea become a writing composition. By using this strategy the students will be able to improve their writing skill. Brainwriting is an alternative method to brainstorming that tries to encourage a more uniform participation within a group. Like brainstorming, it is designed to generate lots and lots of ideas in a short amount of time.

Purpose:This study focuses on an online Arabic learning through synchronous and asynchronous approaches. Meanwhile, the aims of this study are; 1) describing implementation of synchronous and asynchronous online Arabic learning in higher education, 2) investigating its advantages and disadvantages, 3) offering solutions in learning Arabic through e-learning. Design/methodology/approach:This is a descriptive qualitative research that applies an observation method, interview, and documentation to collect the data. Afterwards, identity method is used to investigate the data. Then, triangulation is applied for validity check Findings/result:The result shows that synchronous e-learning is the most widely applied in learning Arabic for IPIREL UMY (75 %) and IPIEF UMY (62%). On the contrary, Arabic learning (IBA) at UINSA tends to apply asynchronous e-learning (75%). Originality/value:It is important for lecturer to prepare the best method and media for distance learning. By understanding what students need, lecturer may determine how important for students to learn Arabic through synchronous or asynchronous approach. Paper type:Research paper

Artificial intelligence has been widely used in various applications such as health and safety, smart homes, greenhouses, and industrial application. It has been increasingly utilized in the industry owing to its benefits in terms of enhancing the overall performance of a given system. This study appeared from a real need in many local industries. In this paper, a prototype system has been implemented for artificial control on the temperature of the industrial panel. The paper includes two control systems executed; classical PID (Proportional Integral Derivative) and fuzzy logic with a comparison between them. Fuzzy control algorithm is developing based on Sugeno method inside PLC (Programmable Logic Controller). The connection of PLC with sensors is used by the Modbus protocol. Arduino UNO and Ethernet shield are used to connect the sensor to the router and then to PLC by Modbus.

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.

In the past two decades, the Internet has become as open, publicly and widely used as a source of data transmission and exchanging the messages between criminals, terrorists and those who have illegal motivations. Moreover, exchanging important data between various military and financial institutions, even ordinary citizens. From this view, there is one of the important means of exchanging information widely used on the Internet medium is e-mail. Email messages are digital evidence that has been become one of the important means to adopt by courts in many countries and societies as evidence relied upon in condemnation. This paper presents a distinct technique for classifying emails based on data processing and mining, trimming, refinement, and then adapts several algorithms to classify these emails and then using SWARM algorithm to obtain practical and accurate results also using hybrid English lexical dictionary SentiWordNet3.0 for email forensic analysis then deal with a machine learning algorithm. The proposed system is capable of learning in an environment with large and variable data. To test the proposed system, have to select available data which Enron Data set. A high accuracy rate (95%) was obtained, which is higher than the classification rates mentioned in previous research papers presented in section 2 in this paper.

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.

Natural language means a language that is used for communication by human. Natural Language Processing (NLP) helps machines to understand the natural language. The natural language for the web pages consists of many semantic relations between entities. Discovering significant types of relations from the web is challenging because of its open nature. In this paper we survey several important types of semantic relations. This paper also covers the relation extraction (RE) approaches which are divided into: supervised approach, which contains Feature base and Kernel base, and the unsupervised approach. Three relation extraction algorithms are discussed: Support Vector Machine (SVM), Genetic algorithm and Naive Bayes classifier This survey would be useful for three kinds of readers First the Newcomers in the field who want to quickly learn about relation extraction. Second the researchers who want to know how the various relation extraction techniques developed over time. Third the trainers who just need to know which RE technique works best in different settings

All areas of business and governmental organizations are currently dependent on information technology (IT) to meet business objectives of improving network service and maximizing limited resources. In this paper the main problems that’s represented by using the information network to transfer information such as text, image and video files, conversations or direct video lectures, periods of use that can cause bottlenecks and network downtime, in addition to the large number of users of the network and the causes of these problems. The main objective of this paper is to find out what methods or means to overcome the problems that guide us in terms of optimal use of resources and components even if it is limited, and to determine which technologies are best depending on the typically, quality, importance and confidentiality of the information and the periods of arrival of the information to be transferred. The information is based on the type of networks adopted if they are localized on a given building or the scope of a city or a wide range to include a country or continent and so on.

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.

The process of improvement software quality began from early stages of software engineering development. It uses multiple quality metrics which are very important in software development. To calculate the standards quality of in software testing has been adopted. The software testing is focusing on the Software defect. In this paper is proposed new methods which combine the particle swarm optimization (PSO) to handle the best features Extraction with back-propagation networks to testing and evaluation of the data set . The paper depended database for NASA standards data. The result and experiment method improved quality performance for all classification methods used in the research"Combining Particle Swarm Optimization based Feature Selection and Bagging for Software Defect Prediction ".

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

This paper studies the manner of energy consumption in Libyan street lighting systems and general road section. It also suggests proposal system with two cases of operation for an attempt to apply the energy saving program by adopting an optimum method in order to decrease the demand of energy in this section and to reduce the use of uneconomic equipment.The proposal system in this paper introduces the Light Emitting Diode (LED) street lighting technology to be used instead of traditional luminaries High Pressure Sodium (HPS). The proposed system is divided into two cases. The first case discusses the replacement of traditional luminaries (HPS) with energy saving luminaries (LED), while second case explains how integrating control node (dynamic dimmer) into LED in order to dim output lighting in streets will save more energy.This study reaches a result that a significant amount of energy of %47 (about 1092.23 GWh/year) of total energy consumed in street lighting sector could be saved if first case is applied. Moreover, it suggests that more energy of %58 (about 1380.02 GWh/year) of total energy consumed in the same sector cloud be saved if the second case is adopted.

Clinical decisions are crucial because they are related to human lives. Thus, managers and decision makers inthe clinical environment seek new solutions that can support their decisions. A clinical data warehouse (CDW) is animportant solution that is used to achieve clinical stakeholders’ goals by merging heterogeneous data sources in a centralrepository and using this repository to find answers related to the strategic clinical domain, thereby supporting clinicaldecisions. CDW implementation faces numerous obstacles, starting with the data sources and ending with the tools thatview the clinical information. This paper presents a systematic overview of purpose of CDWs as well as the characteristics;requirements; data sources; extract, transform and load (ETL) process; security and privacy concerns; design approach;architecture; and challenges and difficulties related to implementing a successful CDW. PubMed and Google Scholarare used to find papers related to CDW. Among the total of 784 papers, only 42 are included in the literature review. Thesepapers are classified based on five perspectives, namely methodology, data, system, ETL tool and purpose, to findinsights related to aspects of CDW. This review can contribute answers to questions related to CDW and providerecommendations for implementing a successful CDW.

The evolution of technology has increased the rate of traffic accidents that occurs frequently causing loss of lifeand property. Therefore, the automatic traffic monitoring system gradually attracted the attention of researchers in improvingtraffic safety through the field of intelligent transport systems. In this paper, a cost-effective approach based on GSM systemfor automatic traffic incident detection is proposed. This paper provides an optimal solution to reduce the death rate by usingthe vibration sensor and GSM system; the implementation system is based on hardware (circuits) and software to build agraphical user interface (GUI) using LabView TM to process the data. Sensors are installed into the vehicles on each side ofthe vehicle. An SMS will be sent to the user after the accident. This system will assist in search and rescue vehicle involved inthe accident.

In this paper, an adaptive integral Sliding Mode Control (SMC) is employed to control the speed of Three-Phase Induction Motor. The strategy used is the field oriented control as ac drive system. The SMC is used to estimate the frequency that required to generates three phase voltage of Space Vector Pulse Width Modulation (SVPWM) invertor . When the SMC is used with current controller, the quadratic component of stator current is estimated by the controller. Instead of using current controller, this paper proposed estimating the frequency of stator voltage since that the slip speed is function of the quadratic current . The simulation results of using the SMC showed that a good dynamic response can be obtained under load disturbances as compared with the classical PI controller, The complete mathematical model of the system is described and simulated in MATLAB/SIMULINK.

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

This paper proposes a hybrid system for secretly embedding images into the dithered multilevelimage. Confident hybridizations between steganography and quantum encryptions are either rare inliterature or suffer a poor effectiveness in secure communication. This paper scrambles and divides thesecret image into groups to be embedded in the blocks of the cover image using three chaos algorithms.These are Lorenz map, Henon map, and Logistic map algorithms. The encryption of embedded imagesconducted using the quantum one-time pad. Results showed that the proposed hybrid system succeeded inembedding and combining images with quantum cryptography algorithms.

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.

The objective of this paper is to develop a parallel Pole numerical integration method suitable for renaming in MIMD computing systems. In this paper we improve the Pole Method for numerical integration by partitioning and parallel processing .we compared the developed methods with initial methods the comparison showed the supervise the developed Method for the initial method. The developed methods are suitable fof running on MIMD computing systems.

Recently the Wavelet Transform has gained a lot of popularity in the field of signal and image processing, this is due to its capability of providing both time and frequency information simultaneously.In this paper, focus on used Discrete Wavelet Transform 2-dimenssion )2D- DWT) based on conventional approach, convolution, to image processing and implementation by using FPGA(Field Programmable Gate Array) ,due to many researches were implemented on this Hardware in recent years ,using VHDL. In this paper, has been proposed two VHDL architectures to implementation the conventional of the Daubechies 5/3-tap biorthogonal filter bank, a simple – straightforward one and an optimized one, substituting the multipliers used for scaling with shift – add operations. The architecture of optimized approaches were designed and implemented on FPGA, type of Xilinx XC3S500E Spartan-3E.

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.

Two new hybrid algorithms have been suggested in this paper, the first one utilizes four formula of self-scaling update matrix was used. The matrix is selected according to Buckley method in each step. The new algorithm has been compared with BFGS standard algorithm by means of (10) multi-dimensional standard functions. As for the second new hybrid algorithm, a new method is used to test the conjugate coefficient (β) which consists of Hestenes Stiefel (HS) and Dai and yuan (DY). Then it is compared with BFGS and PCG algorithms, which uses BFGS update, by means of (10) multi-dimesional standard functions. Numerical results in general indicates the efficiency of the algorithms proposed in this paper by using this number of non-linear functions in this domain.

We solve in this paper some machine scheduling problems with certain conditions; the solution had been made by using dynamic programming procedures with a fixed time for all the algorithms. Some of the algorithms described in the paper represent a modification to some mathematical programming algorithms and some of them are new or a generalization to others. The optimal solution of all these algorithms will be done with a fixed complexity time, which may lead us to solve them easier and faster.

In this paper, we have used one of the preconditioned conjugate gradient algorithm with the Quasi – Newton approximation; namely the BFGS preconditioned algorithm which was suggested by (AL-Bayati and Aref, 2001). In this paper we have suggested a new algorithm for constrained optimization with robust numerical results, for solving constrained optimization problems.

The number of cancer diagnoses and deaths worldwide is rising every year despite technological advancements in diagnosing and treating multiple forms of cancer. An oncolytic virus is a type of tumor-killing virus that can infect and analyze cancer cells while mostly preserving normal cells. The oncolytic Vesicular-Stomatitis Virus therapeutic's cell cycle-specific action mathematically investigated. An optimal Proportion Integral-Derivative (PI-D) controller is introduced in this paper based on a suggested Improved Crow Search Algorithm (ICSA) to enhance the outcome of oncolytic virotherapy. The control technique was tested in a computer using MATLAB simulation. The suggested ICSA is used to tune the parameters of the PI-D controller. The ICSA used the inertia factor and boundary handle mechanism in the position update equation to balance exploration and exploitation. The simulation results show that decrease in total dose, tumor cells to 30%, the tumor remain in the treatment area from day 30 onwards. Furthermore, the ICSA algorithm outperforms the CSA and PSO algorithms by 34.5497×10-6 and 15.2573 ×10-6, respectively, indicating the robustness of treatment methods that can accomplish tumor reduction through biological parameters ambiguity.

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.

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.

Extensible Markup Language (XML) has become a significant technology for transferring data through the world of the Internet. XML labelling schemes are an essential technique used to handle XML data effectively. Labelling XML data is performed by assigning labels to all nodes in that XML document. CLS labelling scheme is a hybrid labelling scheme that was developed to address some limitations of indexing XML data. Moreover, datasets are used to test XML labelling schemes. There are many XML datasets available nowadays. Some of them are from real life datasets and others are from artificial datasets. These datasets and benchmarks are used for testing the XML labelling schemes. This paper discusses and considers these datasets and benchmarks and their specifications in order to determine the most appropriate one for testing the CLS labelling scheme. This research found out that the XMark benchmark is the most appropriate choice for the testing performance of the CLS labelling scheme.

The main drawback of the Orthogonal Frequency Division Multiplexing (OFDM) with Differential Chaos Shift Keying (DCSK) that is named (OFDM-DCSK) is the high Peak to Average Power Ratio (PAPR). In this paper, clipping and companding techniques are suggested to overcome the PAPR problem in the OFDM-DCSK system. For the clipping technique, the clipping function is applied before transmitting the signal without the need for an inverse function at the receiver side. While for companding techniques, the commanding function is applied at the end of the transmitter side and the corresponding decompanding function is applied at the receiver to recover the original signal. Different companding techniques are investigated including Hyperbolic, A-Law, and Mu-Law companding function that are compared with the Palm clipping technique. The MATLAB simulation result shows that the Mu-Law technique has the best PAPR reduction (7.22 dB) with a good bit error rate (BER) performance when the number of subcarriers is equal to 512.

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.

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.

This paper explores the sizing optimization of stand -alone hybrid energy system (HES) in southern Iraq (Thi Qar province) for supply stand-alone households by the electricity. HES consist of three components (solar cell (PV), diesel generator (DG) and battery storage (BS)). Particle swarm optimization (PSO) used in this study for find optimal sizing of the HES to minimizing multi-objective, first objective is to minimizing the total system cost (TSC) that lead to minimizing cost of energy (COE). Second objective is to minimizing total emission CO2 (TECO2). The constraint of the optimization is the reliability (100 %) mean continuous provide the load demand by the electricity. The results of the optimization show the ability the algorithm to minimizing the multi-objective with continuous supply the load by the electricity through life cycle of the project (25) years.

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.

The importance of branch and bound algorithm is the mathematical improvement to find the value of (X) that Maximize or minimize the objective function within a set of feasible solution, as it is reliable on the efficient evaluation of the bounds of regions or branches of the space of the research, whether they are upper or lower. In this paper, we discussed five cases with respect to branching decisions based on network solutions to calculate the nearest link with a short time. From the results, bound and branch algorithm can develop and change the obtaining solutions for the five cases under study.

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.