Dr. Intisar Shadeed Al-Mejibli
@uoitc.edu.iq
University of Information Technology and Communication
The interests of Intisar includes Wireless Sensor Networks, Security, Internet of Things (IoT) and healthcare systems. This includes create and develop new systems which based on the combination of communications, imaging, sensing and human computer interaction technologies targeted at monitor and control vital cases such as system for diagnosis, treatment and monitoring patients without disturbing the quality of lifestyle.
Further, Intisar interests include using Artificial Intelligent techniques to develop solutions for different network issues.
EDUCATION
PhD in Computing and Electronic Systems, School of Computer Science and Electronic Engineering, University of Essex, England, UK
MSc in Computer Science, Computer Science Department, Science College, University of Baghdad, Iraq.
BSc. in Computers Science, Computer Science Department, Science College, University of Baghdad, Iraq
RESEARCH INTERESTS
Wireless Sensor Networks, Security, Internet of Things (IoT) and healthcare systems.
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
Rana Fadhel Atiyah and Intisar Al-Mejibli
AIP Publishing
Intisar Shadeed Al-Mejibli and Nawaf Rasheed Alharbe
Institute of Advanced Engineering and Science
The low-energy adaptive clustering hierarchy (LEACH) protocol has been developed to be implemented in wireless sensor networks (WSNs) systems such as healthcare and military systems. LEACH protocol depends on clustering the employed sensors and electing one cluster head (CH) for each cluster. The CH nodes are changed periodically to evenly distribute the energy load among sensors. Updating the CH node requires electing different CH and re-clustering sensors. This process consumes sensors’ energy due to sending and receiving many broadcast and unicast messages thus reduces the network lifetime, which is regarded as a significant issue in LEACH. This research develops a new approach based on modifying the LEACH protocol to minimize the need of updating the cluster head. The proposal aims to extend the WSN’s lifetime by maintaining the sensor nodes’ energy. The suggested approach has been evaluated and shown remarkable efficiency in comparison with basic LEACH protocol and not-clustered protocol in terms of extending network lifetime and reducing the required sent messages in the network reflected by 15%, and, in addition, reducing the need to reformatting the clusters frequently and saving network resources.
Suphian Mohammed Tariq and I. Al-Mejibli
The Intelligent Networks and Systems Society
: Determining the localization and tracking of sensor nodes in indoor environments is the goal of this study. The difficulty of significant estimation errors in target localization brought on by unpredictable noise in received signal strength indicator (RSSI) readings, particularly in indoor environments, is a major area of research right now. This study proposed a hybrid technique called particle swarm optimization-generalized regression neural network (PSO-GRNN) to improve the sensor nodes' ability to estimate location and target tracking with more precision, as an alternative to conventional RSSI-based strategy. The GRNN algorithm can use the RSSI values as initiation data of the algorithm of GRNN to locate the location and tracing of the target node. An essential component of the GRNN architecture is the spread constant(σ), The method of trial-and-error to select a value of spread constant(σ), which is insecure and does not always yield the best result, is used to choose the parameter. The PSO method is used to determine the optimal GRNN spread constant value. The hybrid PSO-GRNN method was used to overcome these drawbacks and enhance localization and target tracking accuracy without the need for further apparatuses. The tracking algorithm PSO-GRNN the hybrid outperformed the conventional LNSM technique and produced impressive results. Comparing the proposed method to the conventional RSSI, a considerable gain of 87.58% is possible.
Mays Adel Khaki, Intisar Shaheed Al-Mejibli, and Amer S. Elameer
IEEE
The core aim of the internet of things is providing communication capability between huge numbers of different entities “things”. The Abundance feature of connected devices to the emergence of many security challenges for IoT data, which in turn stimulate researchers to search for appropriate solutions. The Blockchain is one of the security technologies which consider as a game changer in safeguarding the internet of things data. Through its impact, it has made the addition of more devices into the Blockchain ecosystem. Boosting the security of devices used in IoT to accelerate the rate of adoption of Blockchain technology. The main aim of this paper is to investigate the current literature to determine how the management of IoT has become independent and widespread doing away with the need of having to rely on one entity in the storage of data in the new technology, Blockchain assumes the role of a database making it different from the storage methods used in the past. In addition to, the authors have organized the utilization of Blockchain in a well-defined structure. Finally, this paper concluded that by utilization of Blockchain results in improved security and distribution using devices such as sensors which are connected efficiently with the aim of coming up with a secure database which gives rise to lots of business opportunities in the future.
I. Al-Mejibli, S. Al-Majeed, J. Karam, C. Adolfo, C. Iqbal, and C. Yalung
Deanship of Scientific Research
Intisar Shadeed Al-Mejibli, Jwan K. Alwan, and Dhafar Hamed Abd
Institute of Advanced Engineering and Science
Currently, the support vector machine (SVM) regarded as one of supervised machine learning algorithm that provides analysis of data for classification and regression. This technique is implemented in many fields such as bioinformatics, face recognition, text and hypertext categorization, generalized predictive control and many other different areas. The performance of SVM is affected by some parameters, which are used in the training phase, and the settings of parameters can have a profound impact on the resulting engine’s implementation. This paper investigated the SVM performance based on value of gamma parameter with used kernels. It studied the impact of gamma value on (SVM) efficiency classifier using different kernels on various datasets descriptions. SVM classifier has been implemented by using Python. The kernel functions that have been investigated are polynomials, radial based function (RBF) and sigmoid. UC irvine machine learning repository is the source of all the used datasets. Generally, the results show uneven effect on the classification accuracy of three kernels on used datasets. The changing of the gamma value taking on consideration the used dataset influences polynomial and sigmoid kernels. While the performance of RBF kernel function is more stable with different values of gamma as its accuracy is slightly changed.
H M Isam, B L Ong, R B Ahmad, M Elshaikh, and I Al-Mejibli
IOP Publishing
Amar A Sakran and
The World Academy of Research in Science and Engineering
Intisar Al-Mejibli and Sura F. Ismail
IOS Press
Intisar Shadeed Al-Mejibli, Dhafar Hamed Abd, Jwan K. Alwan, and Abubaker Jumaah Rabash
IEEE
Hussein A. Mohammed, Baha'a A. M. Al- Hilli, and Intisar Shadeed Al-Mejibli
IOP Publishing
Haider Kadhim Hoomod, Intisar Al-Mejibli, and Abbas Issa Jabboory
IOP Publishing
Intisar Al-Mejibli and Salah Al-Majeed
IEEE
Multiple input multiple output (MIMO) systems, which are suitable for mmWave communications, facilitate building large arrays of communication channel with Reasonable form factors indoor and outdoor communications. In both, indoors and outdoors communications a reasonable coverage can be achieved by the high gains of array. Deploying MIMO systems in frequency-division duplex mode faces the issue of high feedback overhead of channel state information (CSI) to the transmitter. This issue is attributed to the used multiplexing algorithm. From other hand, it is expected that by 2020, all new 5G technologies will be in operation. Hence, it is crucial to investigate and analyze using the MIMO system with orthogonal frequency-division multiplexing OFDM modulation in 5G technology. This research sheds light on the potential challenges of implementing MIMOOFDM in 5G technology. It proposed four models with different number of transmitter and receiver antenna elements in the array. All proposed model used 2 elements per row in transmitter and receiver antenna. The four models are implemented in two cases Line of sight LOS and Non Line of Sight NLOS. The channel rank and condition number of channel matrix are regarded as significant and accurate mathematical indicators which can be used to evaluation MIMO channel technology. The condition number is calculated from the obtained results of four models with rank of channel metrics.
Haider Kadhim Hoomod, Intisar Al-Mejibli, and Abbas IssaJabboory
IEEE
Dhafar Hamed Abd and Intisar Shadeed Al-Mejibli
IEEE
Salah S. Al-Majeed, Intisar S. Al-Mejibli, and Jalal Karam
IEEE
Intisar Al-Mejibli, Martin Colley, and Salah Al-Majeed
Springer Berlin Heidelberg
Intisar Al-Mejibli and Martin Colley
IEEE
Intisar Al-Mejibli and Martin Colley
IEEE
Intisar Al-Mejibli and Martin Colley
IEEE