The Internet of Things (IoT) is an expanding domain that can revolutionize different industries. Nevertheless, security is among the multiple challenges that it encounters. A major threat in the IoT environment is spoofing attacks, a type of cyber threat in which malicious actors masquerade as legitimate entities. This research aims to develop an effective technique for detecting spoofing attacks for IoT security by utilizing feature-importance methods. The suggested methodology involves three stages: preprocessing, selection of important features, and classification. The feature importance determines the most significant characteristics that play a role in detecting spoofing attacks. This is achieved via two techniques: decision tree (DT) and mutual information (MI). For classification, adaptive boosting (AdaBoost), XGBoost and categorical boosting (CatBoosting) are used to categorize incoming data as normal or spoofing. The experimental results indicate the efficiency of the suggested approach for correctly identifying spoofing attacks with high accuracy, fewer false positives, and reduced time needed. By utilizing feature importance and robust classification algorithms, the system can accurately differentiate between legitimate and malicious IoT traffic, thereby improving the overall security of IoT networks. The CatBoost classifier outperformed the AdaBoost and XGBoost classifiers in terms of accuracy.
Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D
... Show MoreClinical keratoconus (KCN) detection is a challenging and time-consuming task. In the diagnosis process, ophthalmologists must revise demographic and clinical ophthalmic examinations. The latter include slit-lamb, corneal topographic maps, and Pentacam indices (PI). We propose an Ensemble of Deep Transfer Learning (EDTL) based on corneal topographic maps. We consider four pretrained networks, SqueezeNet (SqN), AlexNet (AN), ShuffleNet (SfN), and MobileNet-v2 (MN), and fine-tune them on a dataset of KCN and normal cases, each including four topographic maps. We also consider a PI classifier. Then, our EDTL method combines the output probabilities of each of the five classifiers to obtain a decision b
Change detection is a technology ascertaining the changes of
specific features within a certain time Interval. The use of remotely
sensed image to detect changes in land use and land cover is widely
preferred over other conventional survey techniques because this
method is very efficient for assessing the change or degrading trends
of a region. In this research two remotely sensed image of Baghdad
city gathered by landsat -7and landsat -8 ETM+ for two time period
2000 and 2014 have been used to detect the most important changes.
Registration and rectification the two original images are the first
preprocessing steps was applied in this paper. Change detection using
NDVI subtractive has been computed, subtrac
This work involves three parts , first part is manufacturing different types of laminated below knee prosthetic socket materials with different classical laminated materials used in Baghdad center for prosthetic and orthotic (4perlon layers+2carbon fiber layer+4 perlon layers) , two suggested laminated materials(3perlon layers+2carbon fiber layer+3 perlon layers) and (3perlon layers+1carbon fiber layer+3 perlon layers) ) in order to choose perfect laminated socket . The second part tests (Impact test) the laminated materials specimens used in socket manufacturing in order to get the impact properties for each socket materials groups using an experimental rig designed especially for this purpose. The interface pressure between
... Show MoreThis study was conducted in the Department of Employment and Loans at the Ministry of Labor and Social Affairs to indicate the importance and impact of both the empowerment and the functional flexibility in evaluating the performance of the employees. To achieve the objectives of the study, the data was collected through a questionnaire form designed for this purpose based on previous studies. Data obtained for a significant evaluation of the relationship between the components of both the empowerment and the functional flexibility with the components of the evaluation and determining the degree of importance of each component of both the empowerment and functional flexibility for the components of the evaluation by the extractio
... Show MoreThe research aims to know the concept of politic behavior as one of the important behaviours in the different fields and sectors. It is considered to be part of the organizatial work to face the expected risks. It includes two group of factors personal (self –monitors, locus of control ,expectation s of success, perceived job alternatives)and organizational(promotion ,division resources,role ambiguity ,democratic decision)studied by the researcher in the frame of the relationship with the variable of display continuous trust matain which includes two variable (build trust mantain, display trust continuouness)through applied frame by random sample consists of (90)employee at Farouq State
... Show MoreObjective(s): To evaluate the family physicians' practices and to measure its impact upon the quality of family
medicine health care in Baghdad City model primary health care centers.
Methodology: A descriptive study, using the evaluation approach, has evaluated the impact of family physicians'
practices upon quality of healthcare in Baghdad's Model Primary Health Care Centers of Family Medicine. It is
carried out during 15th of May – 20th of August 2017. The study is conducted at five model primary health care
centers of family medicine from two districts; AL-Rusafa and AL-Kurkh. Sample size is calculated to be (76)
family physicians. Convenient sample of (124) patients who are attending these primary health care cen