English العربية کوردی

ئەز   Lailan Muhsin Haji

Assistant Lecturer

Specialties

Operating System

lailan.haji@uoz.edu.krd
07504109949
Iraq , Zakho
0
Awards
15
Published Journal Articles
0
Thesis
0
Training Course

0
Book Chapter
8
Conference
0
Presentation
0
Workshop

Academic Title

Assistant Lecturer

2020-10-11

Published Journal Articles

Engineering, Technology & Applied Science Research (ETASR) (Issue : 5) (Volume : 14)
Enhanced Convolutional Neural Network for Fashion Classification

Fashion items are hard to classify since there are a million variations in style, texture,... See more

Fashion items are hard to classify since there are a million variations in style, texture, and pattern. Image classification is among the noted strengths of convolutional neural networks. This research introduces an improved CNN architecture for fashion classification, utilizing image augmentation and batch normalization to improve model performance and generalization. To make the model more robust, image augmentation techniques like rotation, width and height shift, zoom, and flips were employed. In addition, a Batch Normalization layer is added in the middle, which can help on stabilizing the learning process and accelerating convergence. The proposed model was trained on an augmented dataset, achieving a satisfactory improvement in test accuracy of 91.97% compared to a baseline CNN model, which obtained 88.5% accuracy. According to the results, the image augmentation with the application of Batch Normalization improves the CNN architecture for better effectiveness in fashion classification tasks.

 2024-08
Engineering, Technology & Applied Science Research (Issue : 5) (Volume : 13)
Bitcoin Price Prediction using the Hybrid Convolutional Recurrent Model Architecture

The field of finance makes extensive use of real-time prediction of stock price tools, which... See more

The field of finance makes extensive use of real-time prediction of stock price tools, which are instruments that are put to use in the process of creating predictions. In this article, we attempt to predict the price of Bitcoin in a manner that is both accurate and reliable. Deep learning models, as opposed to more traditional methods, are used to manage enormous volumes of data and to generate predictions. The purpose of this research is to develop a method for predicting stock prices using the Hybrid Convolutional Recurrent Model (HCRM) architecture. This model architecture integrates the advantages of two separate deep learning models: The 1-Dimensional-Convolusional Neural Network (1D-CNN) and the Long-Short Term Memory (LSTM). The 1D-CNN is responsible for the feature extraction, while the LSTM is in charge of the temporal regression. The developed 1D-CNN-LSTM model has an outstanding performance in predicting stock values.

 2023-10
International Journal of Psychosocial Rehabilitation (Issue : 8) (Volume : 24)
GPUs Impact on Parallel Shared Memory Systems Performance

In recent years the graphic processing units (GPUs) programmability has increased and this lead to... See more

In recent years the graphic processing units (GPUs) programmability has increased and this lead to use in several areas. GPUs can tackle enormous data parallel issues at a higher speed than the conventional CPU. Moreover, GPUs considered more affordable and energy-efficient than distributed systems. This paper gives a comprehensive review of the several published studies in the area of the parallel-shared memory based on the GPUs in the last few years. In addition, we represent the necessary computation time and speedup gains provided by different parallel-shared memory strategies. Moreover, in this article, a clear view and a detailed summary of such used algorithms/methods, hardware, and the results obtained of various parallel-shared memory using GPU approaches present in the literature. The maximum speedup as a performance is the main target of such researches where correlation algorithm and techniques were developed in experimental studies are reported.

 2021-05
Asian Journal of Research in Computer Science (Issue : 4) (Volume : 7)
Efficiency of malware detection in android system: A survey

Smart phones are becoming essential in our lives, and Android is one of the most... See more

Smart phones are becoming essential in our lives, and Android is one of the most popular operating systems. Android OS is wide-ranging in the mobile industry today because of its open-source architecture. It is a wide variety of applications and basic features. App users tend to trust Android OS to secure data, but it has been shown that Android is more vulnerable and unstable. Identification of Android OS malware has become an emerging research subject of concern. This paper aims to analyze the various characteristics involved in malware detection. It also addresses malware detection methods. The current detection mechanism utilizes algorithms such as Bayesian algorithm, Ada grad algorithm, Naïve Bayes algorithm, Hybrid algorithm, and other algorithms for machine learning to train the sets and find the malware.

 2021-04
International Journal of Science and Business (Issue : 1) (Volume : 5)
Impact of IoT Frameworks on Healthcare and Medical Systems Performance

Internet of Thing (IoT) is a system of interconnected calculating equipment, electronically and mechanically and... See more

Internet of Thing (IoT) is a system of interconnected calculating equipment, electronically and mechanically and digital equipment delivered with Unique Identifiers and capability of data-transmission through a system without needful of Human-to-Human or Human-to-Computer communication. However, IoMT considered as IoT-program-implementation aimed at medicinal besides healthcare requirements, information gathering also investigation to be studied and observed. This led to proposing extensive scope of fascinating prospective consequences for enterprises: vehicles mileage-sensitivity as well auto-strategy support otherwise prepare it strongly establish in addition description predicted alighting periods towards taking-up travelers. This is due to that its standards are as of now being connected to improve access to the mind, increment the quality of care also, above all decrease the cost of care. An efficient IoT healthcare system aims to give continuous remote checking of patient health conditions, to counteract the basic patient conditions, and to improve personal satisfaction through a smart IoT environment. The trend of this paper is about displaying a detailed survey that addresses the closest previous studies to IoT roles in the healthcare sector. Giving inspiration, confinements looked by specialists, and recommendations proposed to examiners for improving this basic research field, according to detailed comparison among the addressed researches.

 2021-01
IOSR Journal of Computer Engineering (IOSR-JCE) (Issue : 4) (Volume : 22)
An Investigation for Mobile Malware Behavioral and Detection Techniques Based on Android Platform

Nowadays, with portable computation equipment becoming extra commonly depended besides incorporated through extra sensitive structures... See more

Nowadays, with portable computation equipment becoming extra commonly depended besides incorporated through extra sensitive structures such as infrastructure besides armed or regulation implementation. However, is being clearer when considering that malware and other types with cyberattacks attack such portable structures. Malware has always been an issue regarding any technological advances in the world of software. Smartphones and other mobile devices are thus to be expected to face the same problems. In this paper, mobile malware detection techniques presented in details. Furthermore, we have stated the recent techniques of mobile malware detection. Adding to that, these closest works to the paper objective are compared with respect to the based-portal, depended-approach, and significant system’s description points.

 2020-08
Technology Reports of Kansai University (Issue : 5) (Volume : 62)
Impact of Process Execution and Physical Memory- Spaces on OS Performance

The importance of process monitoring applications continues to grow. Generally, many of the developments in... See more

The importance of process monitoring applications continues to grow. Generally, many of the developments in process monitoring are being driven by access to more and more data. Process monitoring is important to understand the variation in a process and to assess its current state. Process monitoring and controlling an organization is of high importance for all process management initiatives. The parallel execution of numerous threads can perform significant increases in performance and overall efficiency in the computer systems. In many computer systems, numerous performance counters are available. For example, performance counters may provide a count of the number of threads executing at a given time. This paper presented an overview of the main research works in the field of the process and thread controlling and monitoring related to physical memory to measure the performance of the operating system. The main finding is that developing strategies needed to make it easy to deal with the monitoring of a large number of data. Furthermore, the used strategies produced improvements of up to 25% and achieved very good results. Besides, the performance of applications with process control executed much faster than without.

 2020-06
Technology Reports of Kansai University (Issue : 5) (Volume : 62)
Big Data: Management, Technologies, Visualization, Techniques, and Privacy

In this review paper, the concept of Big Data will be presented. In the beginning,... See more

In this review paper, the concept of Big Data will be presented. In the beginning, a definition of Big Data its features will be reviewed. Then, the main or the most important issue met in big data management with the steps for data processing will be described. As well, the technologies used with Big Data management will be reviewed. Also, the most important visualization methods and techniques for analyzing big data will be listed and explained. Lastly, what challenges the Big Data is faced for privacy will be described and what you need to design a privacy model.

 2020-06
TEST Engineering & Management (Volume : 83)
Dynamic resource allocation for distributed systems and cloud computing

a system that comprises of self-sufficient computers that are associated utilizing a conveyance middleware is... See more

a system that comprises of self-sufficient computers that are associated utilizing a conveyance middleware is called distributed system.Also, computations-over-Internet are fundamentals in the field of present-day processing frameworks. Where cloud suppliers need to give a successful asset to the clients to expand its QoSThe computations-over-Internet condition relates to the place numerous clients' sign-in, taking in consideration that Internet-resources have to assigned animatedly as focussing on the cost composition. This paper addresses many strategies of resources-assigning depending on QoS efficiency with performing friendly used tasks. Furthermore, interest points, limitations and restrictions for this assigning process will be considered.

 2020-06
TEST Engineering & Management (Volume : 83)
Facial Expression Recognition based on Hybrid Feature Extraction Techniques with Different Classifiers

Facial Expression Recognition (FER) became an important and interest challenging area in the field of... See more

Facial Expression Recognition (FER) became an important and interest challenging area in the field of computer vision. Due to its major application possibilities, FER is an active topic of research papers since the 1990s, also for the same reason, FER has accomplished a high role in the image processing area. Typically, FER is processed in three main stages including face detection, feature extraction or selection, and classification. This study presents an overview of the current work done for the techniques of the FER field and reviews some of the published researches for the last five years till the date. This paper also gives an overview of the customized made FER algorithms and focused on the method of feature extraction of these FER techniques also the databases that are used. The feature extraction techniques played an important role in making these algorithms more efficient.

 2020-05
International Journal of Multidisciplinary Research and Publications (IJMRAP) (Issue : 1) (Volume : 3)
Impact of Load Sharing on Performance of Distributed Systems Computations

Distributed system can be composed of, possibly computing and heterogeneous nodes linked through a communication... See more

Distributed system can be composed of, possibly computing and heterogeneous nodes linked through a communication network. The entire resources of any node supposed to be transparently and easily accessible from other nodes. A critical part of a distributed system design configuration is the decision of a load sharing or global planning procedure. Therefore, workload distribution is one of the most important factors that the performance of distributed systems depends on. This paper gives the reader a conjectural understanding of general compacts of load sharing on the performance of distributed systems. New depended methods of load sharing system are addressed and analyzed based on the models of relationship between the strength and load. Intelligent controllers addressed that depended by pervious researches for optimal reliability, refining the control data simultaneity besides decreasing the control suspension incongruity. Consequently, to manage the load and protect the system from any excess situations based on standard guidelines. It is clear from the previous researches-analyzation that the load sharing approach improves the distributed systems performance by work movement from the heavily loaded nodes into light loaded nodes.

 2020-05
Technology Reports of Kansai University (Issue : 5) (Volume : 62)
Impact of Cloud Computing and Internet of Things on the Future Internet

Internet of Things (IoT) and Cloud computing are extremely distinct technologies which are by now... See more

Internet of Things (IoT) and Cloud computing are extremely distinct technologies which are by now playing an important role in our life. It is expected that adopting and using them would be more and more common, that makes them significant components for the Future Internet (FI). The upcoming internet-associated revolution is almost there with the existence of the IoT. IoT empowers connection and communications among tons of devices between themselves to exchange information, knowledge, and data that promotes the quality of our daily lives. Alternatively, appropriate, upon-request, and adaptable network access is provided by Cloud Computing, as a result, makes it possible to contribute computing resources which helps dynamic data be integrated from a variety of data sources. However, Cloud Computing and IoT in FI cannot be implemented without an abundance of issues and problems. In this research paper, we will be endeavoring to outline and put light on the prime and main concepts of the Cloud Computing and IoT.

 2020-05
TEST Engineering & Management (Issue : 3) (Volume : 83)
Multicomputer Multicore System Influence on Maximum Multi-Processes Execution Time

Multi-core is one of the most significant speed-enhancing trends of processors for getting a boost... See more

Multi-core is one of the most significant speed-enhancing trends of processors for getting a boost in performance. Thus, making the new direction manufacturers are focusing on to be Multi-Core-Processors (MCP). Boosting the multitasking computing-power is one of many advantages of MCP. These kinds of processors provide few complete execution cores instead of one, each with an independent interface to the front side bus. This paper proposes a hybrid memory parallel processing approach combining the activities of (shared memory with distributed) parallel process approaches. This combination provides an efficient parallel processing system with high processing speed and treating with heavy loads. The proposed system consists of client-side (one computer) and server-side (multicomputer). All servers are of MCP type units, connected together via interconnection network, managed and controlled by the distributed system principles. In order to illustrate the real abilities of this system, multiple processes considered to be executed by server-side. The obtained implemented results include Total-Execution-Time (TET), Core-Execution-Time (CET) and Waiting-Time (WT). The proposed system implemented by using C# language.

 2020-05
Technology Reports of Kansai University (Issue : 4) (Volume : 62)
Characteristics and Analysis of Hadoop Distributed Systems

The last days, the data and internet are become increasingly growing which occurring the problems... See more

The last days, the data and internet are become increasingly growing which occurring the problems in big-data. For these problems, there are many software frameworks used to increase the performance of the distributed system. This software is used for available of large data storage. One of the most beneficial software frameworks used to utilize data in distributed systems is Hadoop. This software creates machine clustering and formatting the work between them. The Hadoop consists of two major components which are Hadoop Distributed File System (HDFS) and Map Reduce (MR). By Hadoop, we can process, count and distribute of each word in a large file and know the number of affecting for each of them. In this paper, we will explain what is Hadoop and its architectures, how it works and its performance analysis in a distributed system according to many authors. In addition, assessing each paper and compare with each other.

 2020-04
Science Journal of University of Zakho (Issue : 3) (Volume : 6)
A State of Art Survey for OS Performance Improvement

Through the huge growth of heavy computing applications which require a high level of performance,... See more

Through the huge growth of heavy computing applications which require a high level of performance, it is observed that the interest of monitoring operating system performance has also demanded to be grown widely. In the past several years since OS performance has become a critical issue, many research studies have been produced to investigate and evaluate the stability status of OSs performance. This paper presents a survey of the most important and state of the art approaches and models to be used for performance measurement and evaluation. Furthermore, the research marks the capabilities of the performance-improvement of different operating systems using multiple metrics. The selection of metrics which will be used for monitoring the performance depends on monitoring goals and performance requirements. Many previous works related to this subject have been addressed, explained in details, and compared to highlight the top important features that will very beneficial to be depended for the best approach selection.

 2018-09

Conference

2nd International Conference of Mathematics, Applied Sciences, Information and Communication Technology (ICMAICT_2022)
 2023-12
License Plate Detection and Recognition: A Study of Review

The detection and recognition of automatic license plates (ALPs) is an important task for traffic surveillance and parking management systems, as well as for sustaining the flow of modern civic life. It's been suggested that... See more

The detection and recognition of automatic license plates (ALPs) is an important task for traffic surveillance and parking management systems, as well as for sustaining the flow of modern civic life. It's been suggested that there are a variety of ways to detect and recognize ALPs thus far Image processing and machine learning techniques are typically used in these approaches. For object detection and license plate identification, this article reviews most of the approaches. In order to improve the suitability of the input pictures for subsequent processing, many pre-processing approaches including Gaussian filtering and adaptive image contrast augmentation were examined. Deep semantic segmentation networks and deep learning techniques are also utilized to find the license plate areas in the input picture... For example, deep encoder-decoder network architecture and convolutional neural network (CNN) models used to recognize license plate.

2021 International Conference on Communication & Information Technology (ICICT2021) - Basra – IRAQ
 2021-10
Performance Monitoring for Processes and Threads Execution-Controlling

Strong parallelism can minimize computation time whilst increasing the cost of synchronization. It's vital to keep track of how processes and threads are working. It is understood that thread-based systems improve the productivity of complex... See more

Strong parallelism can minimize computation time whilst increasing the cost of synchronization. It's vital to keep track of how processes and threads are working. It is understood that thread-based systems improve the productivity of complex operations. Threading makes it easier to the main thread to load, thus enhancing system performance. This paper focuses on the development of a system that has two main stages: monitoring and controlling of a program which have ability to run on a number of multicore system architectures, including those with (2, 4, and 8) CPUs. The algorithms associated with this work are built to provide the ability of: providing dependent computer system information, status checking for all existing processes with their relevant information, and run all possible processes/threads cases that compose the user program that might include one of these cases (Single-Processes/Single-Threads, Single-Process/Multi-Thread, Multi-Process/single-Thread, Multi-Process/Multi-Thread and Multi-Process/ Single-Multi-Thread). The monitoring phase provides complete information on User Program (UP) with all its processes and threads, such as (Name, ID, Elapsed Time, Total CPU Time, CPU usage, User Time, Kernel Time, Priority, RAM size, allocated core, read bytes and read count). The controlling phase controls the processes and threads by suspending/resuming/killing them, modifying their priority, and forcing them to a particular core.

2021 International Conference on Communication & Information Technology (ICICT)
 2021-06
Performance Monitoring for Processes and Threads Execution-Controlling

Strong parallelism can minimize computation time whilst increasing the cost of synchronization. It's vital to keep track of how processes and threads are working. It is understood that thread-based systems improve the productivity of complex... See more

Strong parallelism can minimize computation time whilst increasing the cost of synchronization. It's vital to keep track of how processes and threads are working. It is understood that thread-based systems improve the productivity of complex operations. Threading makes it easier to the main thread to load, thus enhancing system performance. This paper focuses on the development of a system that has two main stages: monitoring and controlling of a program which have ability to run on a number of multicore system architectures, including those with (2, 4, and 8) CPUs. The algorithms associated with this work are built to provide the ability of: providing dependent computer system information, status checking for all existing processes with their relevant information, and run all possible processes/threads cases that compose the user program that might include one of these cases (Single-Processes/Single-Threads, Single-Process/Multi-Thread, Multi-Process/single-Thread, Multi-Process/Multi-Thread and Multi-Process/ Single-Multi-Thread). The monitoring phase provides complete information on User Program (UP) with all its processes and threads, such as (Name, ID, Elapsed Time, Total CPU Time, CPU usage, User Time, Kernel Time, Priority, RAM size, allocated core, read bytes and read count). The controlling phase controls the processes and threads by suspending/resuming/killing them, modifying their priority, and forcing them to a particular core.

Third International Conference on Advanced Science and Engineering (ICOASE2020)
 2021-01
COVID-19 Diagnosis Systems Based on Deep Convolutional Neural Networks Techniques: A Review

The rapidly spreading of the viral disease "COVID-19" causes millions of infections and deaths worldwide. It causes a devastating impact on the lifestyle, public health, and the global economy. This motivates the researchers to invent... See more

The rapidly spreading of the viral disease "COVID-19" causes millions of infections and deaths worldwide. It causes a devastating impact on the lifestyle, public health, and the global economy. This motivates the researchers to invent and develop innovative and automated methods to detect COVID-19 at its early stages. It is necessary to isolate the positive cases quickly to prevent this epidemic and treat affected patients. Many diagnosis methods are proposed to perform accurate and fast detection for COVID-19, such as Reverse Transcription-Polymerase Chain Reaction (RT-PCR). The clinical studies indicate that the severity of COVID-19 cases depends on the virus's amount within infected lungs. Chest X-ray (CXR) and Computed Tomography (CT) images are useful imaging methods for diagnosing COVID-19 cases. Deep Convolutional Neural Network (DCNN) is a machine learning technique usually used in computer vision applications. This review focuses on utilizing the DCNN methods for building an automated Computer-Aided Diagnosis (CADs) system to detect and classify the infected cases of the COVID-19 disease accurately and fast. These techniques are used to extracts valuable information by analyzing a massive amount of CXR and CT images that can critically impact on screening of Covid-19. DCNN techniques proved their robustness, potentiality, and advancement by comparing them among the other learning algorithms. It is worth noting that DCNN is an essential tool for supporting the physicians' clinical decisions.

Third International Conference on Advanced Science and Engineering (ICOASE2020)
 2021-01
Queuing Theory Model of Expected Waiting Time for Fast Diagnosis nCovid-19: A Case Study

This Queuing theory analysis has been used in hospitals and other healthcare settings; its use in this sector is not widespread. Consequently, the queue waiting line is an effective scientific tool in the performance of... See more

This Queuing theory analysis has been used in hospitals and other healthcare settings; its use in this sector is not widespread. Consequently, the queue waiting line is an effective scientific tool in the performance of waiting lines analysis. The main parameters used to measure the performance of the systems are the length of the queue line, utilization of the server, and the delays for arrivals. This study aims to avoid others to expose from epidemics such as (nCovid-19), because of becoming a big global problem today in the world. Also, to know the length for the expected and actual waiting times to diagnosis the arrivals to Duhok city. Collection and execution are done within one week with one activity healthcare team’s (HCT) in the main entry Duhok city, port. Data was collected utilize individual conceptions and records from Saturday through to Thursday, which they are the most critical time setting. The main interest in this study was calculating the average waiting time spent after the process to improve arrivals satisfaction using the queuing theory model. The results of this analysis indicate for each citizen checked by the healthcare team may be waiting 32.44 minutes in a queue. Also, was estimate to provide the results of system capabilities with characterization related to the expected waiting time. Finally, Medical staff at the city outlets can estimate; how many arrivals will be waiting in the line and the number of clients that will walk away each day.

3rd International Conference on Engineering Technology and it’s Applications ,3rd ICETA2020, Islamic University, AL-Najaf, Iraq
 2020-08
Performance Measurement of Processes and Threads Controlling, Tracking and Monitoring Based on Shared-Memory Parallel Processing Approach

In this paper, a professional integrated operating system performance measurement system is proposed, designed, and implemented in order to monitor processes and threads. Because monitoring itself is not enough, so this system provides full control... See more

In this paper, a professional integrated operating system performance measurement system is proposed, designed, and implemented in order to monitor processes and threads. Because monitoring itself is not enough, so this system provides full control of the CPU forcing, Priority-changing, and pausing-resuming-killing of these processes/threads. During these complex operations, it provides the ability to measure/compute the details of Total-execution-time, CPU-time, User-time, Kernel-time, context switching, CPU-usage, and the priority of processes/threads. The proposed system can be used with any architecture of multicore processors. Despite that measuring all these parameters in one system is very difficult and complex especially the Kernel-time and Context-switching, but all of them have been applied and determined successfully. Adding to the above features that never been integrated (by any previous work) in one system, and in order to illustrate the real abilities of this system, a shared-memory parallel processing approach has been proposed and applied. The proposed system prepared to run all possible cases of processes and threads that construct under-tested-program which may be one of the: Single-Process-Single-Thread, Single-Process-Multi-Thread, Multi-Process-Single-Thread, Multi-Process-Multi-Thread, and Multi- Process-Single-Multi-Thread. The algorithms of this system are designed and implemented via C++ programming language(using C++ Standard Library Thread) which is the nearest programming to the OSs provides a more increasing processing speed.

ICMAICT 2020
 2020-06
Design and Implementation of Electronic Enterprise University Human Resource Management System

Electronic Human Resource Management System (EHRMS) is a paperless-based system, which plays a vital role in facilitating organizational processes, overcoming all obstacles of a paper-based system, reducing cost, time, and efforts, enhancing the quality of... See more

Electronic Human Resource Management System (EHRMS) is a paperless-based system, which plays a vital role in facilitating organizational processes, overcoming all obstacles of a paper-based system, reducing cost, time, and efforts, enhancing the quality of services (QoS), and providing more accurate data. In addition, it is beneficial for competitive advantages and it eases the tasks of the HR managers to make decisions. In this paper, an efficient EHRMS is proposed, designed, and implemented. The system is called Enterprise Electronic University Human Resource Management System (EEUHRMS). The proposed system consists of fourteen modules that provide four groups of services. The first group is related to applicant services: Online Recruitment. The second group is related to staff services: Registration, Acknowledgements/Punishments, Annual Premium, Leaves, Leave Deduction, Archive, Dispatch, Extra Fees, Salary, and Service Summary. The third group is related to institutions and presidency services: Post and Statistics. While the fourth group is related to university services: Authentication and Statistics. The proposed system is evaluated by using the System Usability Scale (SUS) to get results via specific questionnaires that are checked by the university staff. The evaluation score of the questionnaire was about (85) which is considered a good result. The proposed system is developed using the Laravel framework.

ICMAICT 2020
 2020-06
Design and Implementation of Electronic Enterprise University Human Resource Management System

Electronic Human Resource Management System (EHRMS) is a paperless-based system, which plays a vital role in facilitating organizational processes, overcoming all obstacles of a paper-based system, reducing cost, time, and efforts, enhancing the quality of... See more

Electronic Human Resource Management System (EHRMS) is a paperless-based system, which plays a vital role in facilitating organizational processes, overcoming all obstacles of a paper-based system, reducing cost, time, and efforts, enhancing the quality of services (QoS), and providing more accurate data. In addition, it is beneficial for competitive advantages and it eases the tasks of the HR managers to make decisions. In this paper, an efficient EHRMS is proposed, designed, and implemented. The system is called Enterprise Electronic University Human Resource Management System (EEUHRMS). The proposed system consists of fourteen modules that provide four groups of services. The first group is related to applicant services: Online Recruitment. The second group is related to staff services: Registration, Acknowledgements/Punishments, Annual Premium, Leaves, Leave Deduction, Archive, Dispatch, Extra Fees, Salary, and Service Summary. The third group is related to institutions and presidency services: Post and Statistics. While the fourth group is related to university services: Authentication and Statistics. The proposed system is evaluated by using the System Usability Scale (SUS) to get results via specific questionnaires that are checked by the university staff. The evaluation score of the questionnaire was about (85) which is considered a good result. The proposed system is developed using the Laravel framework.