2023-12

2nd International Conference of Mathematics, Applied Sciences, Information and Communication Technology (ICMAICT_2022)

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.

2021-10

2021 International Conference on Communication & Information Technology (ICICT2021) - Basra – IRAQ

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.

2021-06

2021 International Conference on Communication & Information Technology (ICICT)

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.

2021-01

Third International Conference on Advanced Science and Engineering (ICOASE2020)

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.

2021-01

Third International Conference on Advanced Science and Engineering (ICOASE2020)

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.

2020-08

3rd International Conference on Engineering Technology and it’s Applications ,3rd ICETA2020, Islamic University, AL-Najaf, Iraq

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.

2020-06

ICMAICT 2020

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.

2020-06

ICMAICT 2020

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.