Papers by Zinah Sattar Jabbar
Periodicals of Engineering and Natural Sciences (PEN), May 10, 2023
Currently, private universities are making significant efforts to keep up with changing market de... more Currently, private universities are making significant efforts to keep up with changing market demands and societal expectations, particularly in an environment that is rapidly evolving such as Baghdad, Iraq. In order to maintain high standards and achieve excellence, they must continuously seek out the most effective practices and strategies for success. Strategic management has been demonstrated to be an efficient tool for enhancing institutional performance, and the university's organizational culture, which is comprised of traditional institutional elements, is recognized as a significant factor in how organizations operate. Through the utilization of strategic thinking as a mediator, this research aims to evaluate and clarify how organizational culture impacts institutional excellence. A simple random sample was employed to gather information from individuals in managerial positions across multiple sections. Structural Equation Modeling (SEM) was employed to explain the variables under examination. The outcomes and analyses reveal a high level of relative proportions for the variables under investigation and indicate an indirect relationship between the independent and dependent variables. This research recommends several important suggestions and proposes additional research avenues for further investigation
Periodicals of Engineering and Natural Sciences (PEN), May 10, 2023
The enormous growth in demand for WBAN services has resulted in a new set of security challenges.... more The enormous growth in demand for WBAN services has resulted in a new set of security challenges. The capabilities of WBAN are developing to meet these needs. The complexity, heterogeneity, and instability of the mobile context make it difficult to complete these duties successfully. A more secure and flexible WBAN setting can be attained using a trust-untrust nodes classification, which is one method to satisfy the security needs of the WBAN. Considering this, we present a novel Deep Learning (DL) approach for classifying WBAN nodes using spatial attention based iterative DBN (SA-IDBN). Z-score normalization is used to remove repetitive entries from the input data. Then, Linear Discriminate Analysis (LDA) is employed to retrieve the features from the normalized data. In terms of accuracy, latency, recall, and f-measure, the suggested method's performance is examined and contrasted with some other current approaches. Regarding the classification of WBAN nodes, the results are more favorable for the suggested method than for the ones already in use.
Periodicals of Engineering and Natural Sciences (PEN), May 10, 2023
In response to user demand for wearable devices, several WBAN deployments now call for effective ... more In response to user demand for wearable devices, several WBAN deployments now call for effective communication processes for remote data monitoring in real time. Using sensor networks, intelligent wearable devices have exchanged data that has benefited in the evaluation of possible security hazards. If smart wearables in sensor networks use an excessive amount of power during data transmission, both network lifetime and data transmission performance may suffer. Despite the network's effective data transmission, smart wearable patches include data that has been combined from several sources utilizing common aggregators. Data analysis requires careful network lifespan control throughout the aggregation phase. By using the Nomadic People Optimizer-based Energy-Efficient Routing (NPO-EER) approach, which effectively allows smart wearable patches by minimizing data aggregation time and eliminating routing loops, the network lifetime has been preserved in this research. The obtained findings showed that the NPO method had a great solution. Estimated Aggregation time, Energy consumption, Delay, and throughput have all been shown to be accurate indicators of the system's performance.
Periodicals of Engineering and Natural Sciences (PEN), May 10, 2023
When evaluating an Internet of Things (IoT) platform, it is crucial to consider the quality of se... more When evaluating an Internet of Things (IoT) platform, it is crucial to consider the quality of service (QoS) as a key criterion. With critical devices relying on IoT technology for both personal and business use, ensuring its security is paramount. However, the vast amount of data generated by IoT devices makes it challenging to manage QoS using conventional techniques, particularly when attempting to extract valuable characteristics from the data. To address this issue, we propose a dynamic-progressive deep reinforcement learning (DPDRL) technique to enhance QoS in IoT. Our approach involves collecting and preprocessing data samples before storing them in the IoT cloud and monitoring user access. We evaluate our framework using metrics such as packet loss, throughput, processing delay, and overall system data rate. Our results show that our developed framework achieved a maximum throughput of 94%, indicating its effectiveness in improving QoS. We believe that our deep learning optimization approach can be further utilized in the future to enhance QoS in IoT platforms.
Quantum optics in visual sensors and adaptive optics by quantum vacillations of laser beams wave propagation apply in data mining
Optik
An Efficient E-ticket Fare Scheme for Passengers Based on the Distance Traveled Between Entry Point and Exit Point
Communications in Computer and Information Science, 2018
This scheme determines the ticket price a passenger should pay based on the amount of distance tr... more This scheme determines the ticket price a passenger should pay based on the amount of distance traveled in each trip. The recent technology can assist to decrease the price of e-tickets as well as to enhance a control of the passenger movements. The proposed scheme provides robust privacy to non-fraud passengers, meaning that the authorized service provider is unable to reveal id of the passengers. Furthermore, various trips cannot be linked to the same passenger among themselves. But, such schemes should be protected from cheating and also protect passenger privacy. It means that the authorized service provider cannot be revealing id of passengers. But, the pseudonym of the passenger can be revoked when he cheats. The proposed scheme has been implemented and its results have been rated. The initial outcomes given in this paper appear very promising. The outcomes show that the scheme is applicable and will give good results in case of application to new generations of mobile phones. Also, the results show that the method is more efficient and faster than the already existing schemes.
International Journal of Innovative Technology and Exploring Engineering, 2019
This paper proposes a new card game and dealing system, designed specifically for poker games. Th... more This paper proposes a new card game and dealing system, designed specifically for poker games. The proposed method benefits from two poker characteristics games that are ignored by public card systems. First, cards are dealt in poker games in the form of rounds, betting with them, instead of all at once. Second, the total number of cards dealt in poker game cards is depending on the number of players but is usually less than half the total. With these remarks in mind, the proposed method distributes the computing cost of dealing cards evenly across the rounds. Compared to systems that provide a full introduction to the deck, the proposed approach provides a significant reduction in the total cost of computing. Also, it’s fair and strong. It perfectly fits hardware such as smartphones. The presented system is fast and secure mental poker protocol. It is twice as fast as similar protocols.
Bulletin of Electrical Engineering and Informatics, Feb 1, 2023
Network attacks (i.e., man-in-the-middle (MTM) and denial of service (DoS) attacks) allow several... more Network attacks (i.e., man-in-the-middle (MTM) and denial of service (DoS) attacks) allow several attackers to obtain and steal important data from physical connected devices in any network. This research used several machine learning algorithms to prevent these attacks and protect the devices by obtaining related datasets from the Kaggle website for MTM and DoS attacks. After obtaining the dataset, this research applied preprocessing techniques like fill the missing values, because this dataset contains a lot of null values. Then we used four machine learning algorithms to detect these attacks: random forest (RF), eXtreme gradient boosting (XGBoost), gradient boosting (GB), and decision tree (DT). To assess the performance of the algorithms, there are many classification metrics are used: precision, accuracy, recall, and f1-score. The research achieved the following results in both datasets: i) all algorithms can detect the MTM attack with the same performance, which is greater than 99% in all metrics; and ii) all algorithms can detect the DoS attack with the same performance, which is greater than 97% in all metrics. Results showed that these algorithms can detect MTM and DoS attacks very well, which is prompting us to use their effectiveness in protecting devices from these attacks.
Bulletin of Electrical Engineering and Informatics, 2023
Network attacks (i.e., man-in-the-middle (MTM) and denial of service (DoS) attacks) allow several... more Network attacks (i.e., man-in-the-middle (MTM) and denial of service (DoS) attacks) allow several attackers to obtain and steal important data from physical connected devices in any network. This research used several machine learning algorithms to prevent these attacks and protect the devices by obtaining related datasets from the Kaggle website for MTM and DoS attacks. After obtaining the dataset, this research applied preprocessing techniques like fill the missing values, because this dataset contains a lot of null values. Then we used four machine learning algorithms to detect these attacks: random forest (RF), eXtreme gradient boosting (XGBoost), gradient boosting (GB), and decision tree (DT). To assess the performance of the algorithms, there are many classification metrics are used: precision, accuracy, recall, and f1-score. The research achieved the following results in both datasets: i) all algorithms can detect the MTM attack with the same performance, which is greater than 99% in all metrics; and ii) all algorithms can detect the DoS attack with the same performance, which is greater than 97% in all metrics. Results showed that these algorithms can detect MTM and DoS attacks very well, which is prompting us to use their effectiveness in protecting devices from these attacks.
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Papers by Zinah Sattar Jabbar