Data mining has the most important role in healthcare for discovering hidden relationships in big datasets, especially in breast cancer diagnostics, which is the most popular cause of death in the world. In this paper two algorithms are applied that are decision tree and K-Nearest Neighbour for diagnosing Breast Cancer Grad in order to reduce its risk on patients. In decision tree with feature selection, the Gini index gives an accuracy of %87.83, while with entropy, the feature selection gives an accuracy of %86.77. In both cases, Age appeared as the most effective parameter, particularly when Age<49.5. Whereas Ki67 appeared as a second effective parameter. Furthermore, K- Nearest Neighbor is based on the minimum error rate, and the test maximum accuracy for K_value selection with an accuracy of 86.24%. Where the distance metric has been assigned using the Euclidean approach. From previous models, it seems that Breast Cancer Grade2 is the most prevalent type. For the future perspective, a comparative study could be performed to compare the supervised and unsupervised data mining algorithms.
The increasing complexity of assaults necessitates the use of innovative intrusion detection systems (IDS) to safeguard critical assets and data. There is a higher risk of cyberattacks like data breaches and unauthorised access since cloud services have been used more frequently. The project's goal is to find out how Artificial Intelligence (AI) could enhance the IDS's ability to identify and classify network traffic and identify anomalous activities. Online dangers could be identified with IDS. An intrusion detection system, or IDS, is required to keep networks secure. We must create efficient IDS for the cloud platform as well, since it is constantly growing and permeating more aspects of our daily life. However, using standard intrusion
... Show MoreIn this research a proposed technique is used to enhance the frame difference technique performance for extracting moving objects in video file. One of the most effective factors in performance dropping is noise existence, which may cause incorrect moving objects identification. Therefore it was necessary to find a way to diminish this noise effect. Traditional Average and Median spatial filters can be used to handle such situations. But here in this work the focus is on utilizing spectral domain through using Fourier and Wavelet transformations in order to decrease this noise effect. Experiments and statistical features (Entropy, Standard deviation) proved that these transformations can stand to overcome such problems in an elegant way.
... Show MoreBotnet detection develops a challenging problem in numerous fields such as order, cybersecurity, law, finance, healthcare, and so on. The botnet signifies the group of co-operated Internet connected devices controlled by cyber criminals for starting co-ordinated attacks and applying various malicious events. While the botnet is seamlessly dynamic with developing counter-measures projected by both network and host-based detection techniques, the convention techniques are failed to attain sufficient safety to botnet threats. Thus, machine learning approaches are established for detecting and classifying botnets for cybersecurity. This article presents a novel dragonfly algorithm with multi-class support vector machines enabled botnet
... Show MoreThe widespread use of the Internet of things (IoT) in different aspects of an individual’s life like banking, wireless intelligent devices and smartphones has led to new security and performance challenges under restricted resources. The Elliptic Curve Digital Signature Algorithm (ECDSA) is the most suitable choice for the environments due to the smaller size of the encryption key and changeable security related parameters. However, major performance metrics such as area, power, latency and throughput are still customisable and based on the design requirements of the device.
The present paper puts forward an enhancement for the throughput performance metric by p
... Show MoreThe present study was carried to evaluate antibacterial activity of Acetone, Alcholic (cold and hot) and Aqueaus(water) extracts of Citrus aurantifoliaseeds,against growth of some bacteria isolated from burns infections(Pseudomonas aeruginosa,Escherichia coli, Klebsiellapneumonia,Staphylococcusaureus)fromKindy HospitalIn Baghdad from March to June 2012.Antibiotic Sensitivity was done for all isolated bacteria used in this study.Results showed variation in antibacterial activity of different extracts against all tested bacteria by well diffusion technique in agar and measuring the diameter of inhibition zone, at concentration 250Mg-ml. Acetone extract had the greatest inhibitory effect followed by hot alcoholci extract, and then cold alcohol
... Show MoreThe research aims to prepare a preliminary feasibility study that shows the importance of preliminary feasibility study in investment decision making, carrying out of the local demand of service provided in accordance with international standards and statement of investment opportunities available to the private sector in several investment methods. In order to reach the objectives of the study was adopted as a method of partial analysis at the level of economic unity through the study demand, supply, costs, economic and social profitability.
The health sector in Iraq is one of the service sectors facing today a continuous deficiency
... Show MoreThis research will deal in a simple way with the concept of urban expansion and taking the decision to sign the spatial signature of residential investment projects in order to reach through them in a real way to the extent of the proportionality of the decision taken, in light of the fulfillment of the conditions that must be met in the matter of making the decision of the spatial signature of the residential investment project and the extent of commitment to them, in which the conditions are: (Ease of access to services and transportation, adequacy of services, commitment to urban land uses) when establishing the investment project represented by the Al-Ayad residential project in the Hittin neighborhood of Al
... Show MoreGastrointestinal diseases and especially chronic gastritis are mainly induced by Helicobacter pylori infection, and provides the basis for gastric carcinogenesis and colorectal cancer. The study involved the detection of serum anti-H. pylori IgG and IgA antibody of and some serum biomarkers ;CEA and CA19-9 in patients with gastrointestinal diseases. Fifty eight serum samples were collected from 25 males and 33 females .Peripheral venous blood was collected from each patient and sera obtained by centrifugation. Serum anti-H. pylori IgG and IgA ,serum CEA and CA19-9 were evaluated by enzyme-linked immunoadsorbent assays (ELISA).Forty eight serum samples were positive for IgG (82.7% ) divided int
... Show MoreThis study was conducted to determine the fungal cause and bio control of damping off and root rot of wheat plants by using pseudomonas fluorescens under greenhouse and field conditions. Results showed isolation of eight species from the soil and roots to deferent region of Baghdad government. Rhizoctonia solani (Rs) and Fusarium solani (Fs) were the predominant damping off fungus with frequency 60 and 52% respectively. Led the using of bacteria formulations such as crud suspension , pure bacteria filtration and pure living cells in culture medium inhibit all type fungi with rates ranging from 84-96% , 80- 93% and 75-88% respectively. Rs and Fs were more pathogenesis under greenhouse conditions, with incidence of 80 and 68% and disease s
... Show MoreThe aim of this study was to assess the effectiveness of listening to music or Quran in reducing cancer patients’ anxiety before chemotherapy administration. Reducing anxiety in people with cancer, prior to chemotherapy administration, is a crucial goal in nursing care.
An experimental comparative study was conducted.
A simple randomization sampling method was applied. Two hundred thirty‐eight people with cancer who underwent chemotherapy were participated. They are assigned as Quran, music and control groups.