Eman Salih Al-Shamery

University of Babylon · Department of Software

The data stream is considered the backbone of many real-world applications. These applications are most effective when using modern techniques of machine learning like deep neural networks (DNNs). DNNs are very sensitive to set parameters, the most prominent one is the learning rate. Choosing an appropriate learning rate value is critical because i...

Emails have become a common modality to exchange messages and information over the internet. Some emails are frequently received from malicious senders, which can lead to several problems. Thus, there is an urgent need to develop reliable and powerful methods for filtering such emails. In this paper, we present a new approach to filter emails to sp...

Data streams are a modern type of data that differ from traditional data in various characteristics: their indefinite size, high access, and concept drift due to their origin in non-stationary environments. Data stream clustering aims to split these data samples into significant clusters, depending on their similarity. The main drawback of data str...

Today sensors represent one of the most important applications for generating data stream. This data has a number of unique characteristics, including fast data access, huge volume, as well as the most prominent feature, the concept drift. Machine learning in general and deep learning technique in particular is among the predominant and successful...

Due to the vast number of stocks and the multiple appearances of developing investment portfolios, investors in the financial market face multiple investment opportunities. In this regard, the investor task becomes extremely difficult as investors define their preferences for expected return and the amount to which they want to avoid potential inve...

computer tasks. Machine Learning (ML) as an essential type of AI and deep learning (DL) is merely a branch of (ML). DL can mainly be helping to fast analysis of the medical images, especially the complex images, and this can speed up an early diagnosis of diseases. The Covid-19 pandemic has spread rapidly within societies, creating real panic for a...

Abstract Real protein interaction network (PIN) is dynamic. Researchers created dynamic PIN by combining static PIN with gene expression data to explain the dynamicity evolution of protein interactions. However, all available approaches failed to recognize low- or high-expression proteins as active proteins. Therefore, determining an adequate thres...

Machine learning approaches are powerful techniques commonly employed for developing cancer prediction models using associated gene expression and mutation data. This manuscript provides a comprehensive review of recent cancer studies that have employed gene expression data from several cancer types (breast, lung, kidney, ovarian, liver, central ne...

Regular E-voting systems for elections may count the votes in less time,less cost,save the privacy of citizens,but still considered risky as votes can be tampered.E-voting systems based on a network distributed ledger show fast results,more trusted,save privacy,cannot be tampered,and distributed in which no central organization controls the syst...

Stock market prediction is an interesting financial topic that has attracted the attention of researchers for the last years. This paper aims at improving the prediction of the Iraq-Stock-Exchange (ISX) using a developed method of feedforward Neural-Networks based on the Quasi-Newton optimization approach. The proposed method reduces the error fact...

Many different applications in the real world can generate huge amount of data, that has unconventional features including massive size, fast access, besides the evolving in its nature; this is data stream. Data stream clustering algorithms began to grow at breakneck speed. evolving Cauchy (eCauchy) is a significant algorithm of density-based data...

Data stream is concerned in industry engineering, finance, economy, traffic and many other fields. The main challenging problems in stream are changed stream with time ,time of data arrival and space required for storage stream. Prediction in stream is used to forecast the new data from available data. An Adaptive Regression Neural Network (ARNN) i...

Defining protein complexes by analysing the protein–protein interaction (PPI) networks is a crucial task in understanding the principles of a biological cell. In the last few decades, researchers have proposed numerous methods to explore the topological structure of a PPI network to detect dense protein complexes. In this paper, the overlapping pro...

Defining protein complexes in the cell is important for learning about cellular processes mechanisms as they perform many of the molecular functions in these processes. Most of the proposed algorithms predict a complex as a dense area in a Protein–Protein Interaction (PPI) network. Others, on the other hand, weight the network using gene expression...

div> Dialog state tracking (DST) plays a critical role in cycle life of a task-oriented dialogue system. DST represents the goals of the consumer at each step by dialogue and describes such objectives as a conceptual structure comprising slot-value pairs and dialogue actions that specifically improve the performance and effectiveness of dialogue sy...

Election is an important event in all countries. Conventional voting suffers many issues, such as cost of time and efforts needed for tallying and counting results, cost in papers, arrangements and all that it takes for a voting process to be achieved. Many countries such as Australia, Belgium, Brazil, Canada, Estonia, France, Germany, India, Italy...

The outbreak of Coronavirus is the most significant global crisis since World War II. Therefore, it is imperative to keep track of the number of infected patients. In -this research, a forecasting technique was performed to forecast the impact of the pandemic in the near future. The study focuses on the daily new affirm cases from badly hit countri...

Customer churn prediction models aim to indicate the customers with the high tendency to churn, allowing for improved efficiency of customer retention operations and reduced costs associated with the attrite event. This paper proposed a data mining model to predict churn customers using Call Detail Records (CDR) data in the Telcom industry. CDR dat...

: Churner Customer is a main tricky and one of the most important issues for large companies, due to the straight impact on the incomes of the companies especially in the telecom domain, companies are searching for advance strategies to predict churn/non-churn customer. This research focuses on the construction of a predictive model to identify eac...

A major and demanding issue in the telecommunications industry is the prediction of churn customers. Churn describes the customer who is attrite from one Telecom service provider to competitors searching for better services offers. Companies from the Telco sector frequently have customer relationship management offices it is the main objective in h...

p>Communication by email is counted as a popular manner through which users can exchange information. The email could be abused by spammers to spread suspicious content to the Internet users. Thus, the need to an effective way to detect spam emails are becoming clear to keep this information safe from malicious access. Many methods have been develo...

Consumption of medicines for a particular disease can be an indicator of the spread of the disease, as the increase in the consumption of medicines implies an increase in the incidence of the disease. Acquired immunodeficiency syndrome (AIDS) is a chronic, potentially life-threatening condition caused by the human immunodeficiency virus (HIV). AIDS...

The provision of pharmaceutical drugs in quantities appropriate to consumption is an important point in the pharmaceutical industry and storage of medicines, as the production of large quantities of unnecessary drugs leads to a longer storage of drugs. Meanwhile, most medicines have a short shelf life. When the amount of production is less than req...

Complex networks provide means to represent different kinds of networks with multiple features. Most biological, sensor and social networks can be represented as a graph depending on the pattern of connections among their elements. The goal of the graph clustering is to divide a large graph into many clusters based on various similarity criteria’s....

DNA sequence alignment is an important and challenging task in computational biology, which is used for finding the optimal arrangement between two sequences. In this paper, an Improved genetic algorithm (GA) is proposed to solve the problem of pairwise sequence alignment. GA is a class of evolutionary algorithms which can be applied as an optimiza...

The main target of this research is to predict churners and non-churners customers in Telecom sector based on project pursuit Random Forest (PPForest) that use discriminant feature analysis as a novelty extension of the conventional Random Forest approach for learning oblique Project Pursuit tree (PPtree). The proposed methodology leverages the adv...

Drug consumption data needs to be linked to the disease. The process of analyzing quantities consumed based on the drug name and brand is complex. It needs to be accurate because it is involved in the provision, manufacture, and marketing of medicines. The aim of this paper is to obtain optimal clustersof the drugs according to utilization. Anew mo...

Speaker recognition is one of the important biometrics methods that have entered into many applications such as security, marketing service, and bank transfers. The main aim of this paper is to identify the speaker with high accuracy through his or her voice. All previous research deal with recorded files for speakers as only sound signals. This re...

DNA sequence alignment is an important and challenging task in Bioinformatics, which is used for finding the optimal arrangement between two sequences. In this paper, two methods are proposed in two stages to solve the pairwise sequence alignment problem. The first method is Matching Regions(MR) concerns on splitting the DNA into regions with adapt...

The control of inflation rate is at the core of monetary policy making. Therefore, there is very great interest in reliable inflation forecasts by central bankers to help them achieve this aim. The aim of this investigation has been to forecast inflation in case of the United States as accurately as possible. This paper proposes a new forecasting m...

Social networks as a domain of complex networks that can be represented as graphs according to the patterns of connections among their elements. Social Communities are a set of nodes with denser connections inside community structures than outside. The goal of graph clustering is to divide the large graph into many clusters depending on multiple si...

The control of inflation rate is at the core of monetary policymaking. Therefore, there is very great interest in reliable i nflation forecasts by central bankers to help them achieve this aim. The aim of this investigation has been to forecast i nflation in case of the United States as accurately as possible. This paper proposes a new forecasting...

Natural language understanding (NLU) module is a critical component in dialogue systems. These programs interact with the human in natural language. The purpose of NLU is to translate user text into a formula that computer can understand. NLU naturally includes identifying a user’s intent often mentioned in intent detection and extracting semantic...

In the health care sector predict the type or severity of the diseases is important for helping people to know their health stability and find solution for any negative indicator. This paper aims to improve prediction of the diseases by exploiting Modified Rough Set (MRS) for features selection which it is proposed as a new method and employing a M...

Crude oil holds a vital and growing role in the local and global economy. The main goal of this study is to explore the effect of technical indicators in enhancing the capability of Sequential Minimal Optimization (SMO) to forecast the precise oil price. In addition, Relief algorithm reduces the dimensional space and eliminates irrelevant factors....

Stock market prediction is an interest financial topic that has attracted the attention of researchers for the last years. Data mining has been effectively used in financial predicting hence researchers have explored technical indicators to optimize the parameters. The main objective of this paper is to improve prediction for stock market using a d...

The Stock Market (SM) prediction price is one of an interesting field at present because it is a chaotic, non-linear, dynamic, non-stationary, noisy and quite difficult. Data mining has been effectively used in stock predicting hence researchers have explored Technical Indicators (TIs) to optimize the parameters. The main objective of this paper is...

Stock Market (SM) prediction is an interesting financial topic that has attracted the attention of researchers for the last years. SM dataset is a chaotic, nonlinear, dynamic, nonstationary, noisy in behavior and quite difficult. The aim of this paper is to predict the future SM price. The proposed system consists of three major stages; the first s...

In this paper, a developed Genetic Algorithm (dGA) has been proposed as an efficient method to find optimal distribution of network connections. There are many network devices can be used as a terminal station such as computers, hubs, routers or wireless networks. The proposed algorithm depends on the modifying of the traditional genetic algorithm...

Customer Churn Prediction model (CCP)aims to detect customers with a high propensity to leave. The target of this research is to handle a large scale Telecommunication Company and identify potential churn. In the proposed research, Predictive Mean Matching (PMM) algorithm used to handle missing values, instead of removing features or observations w...

In this paper a new approach of rough set features selection has been proposed. Feature selection has been used for several reasons a) decrease time of prediction b) feature possibly is not found c) present of feature case bad prediction. Rough set has been used to select most significant features. The proposed rough set has been applied on heart d...

Multiple Sequences Alignment(MSA) is the one of the most important Research themes in bioinformatics. In this research the goal is to identify the best between the two methodologies(Dynamic Programming and Genetic Algorithm). The execution time of Dynamic Programming (DP)algorithm is Growing especially when the number of join operations in a query...

The simplest description of a plagiarism is either a 'copy and paste' for a text even if the source was cited or a change in some words by taking the meaning without citing the source, where determining the meaning is the hardest and most complex task. Plagiarism can be seen as one of the cybercrime, similar to (computer viruses, computer hacking,...

Background: Multiple Sequences Alignment (MSA) is the one of the most important research themes in bioinformatics as well known that the Genetic Algorithm (GA) working on finding the optimal solution, but it may take long generations to get to the solution and this is a problem especially in protein. Methods: In this research the dataset has been u...

The lost values are a common problem in many pivotal real application like data-mining machine learning and pattern detection algorithms. In now days ,there are huge streams of information which contain a missing values for many reasons for instance a malfunction in a piece of equipment, a tissue section on a slide was not stained properly,a techni...