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GIS as A Tool for Expansive Soil Detection at Sulaymaniyah City
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Geotechnical engineering like any other engineering field has to develop and cope with new technologies. This article intends to investigate the spatial relationships between soil’s liquid limit (LL), plasticity index (PI) and Liquidity index (LI) for particular zones of Sulaymaniyah City. The main objective is to study the ability to produce digital soil maps for the study area and determine regions of high expansive soil. Inverse Distance Weighting (IDW) interpolation tool within the GIS (Geographic Information System) program was used to produce the maps. Data from 592 boreholes for LL and PI and 245 boreholes for LI were used for this study. Layers were allocated into three depth ranges (1 to 2, 2 to 4 and 4 to 6) m. A total of 1396 observations were used for producing the maps for both LL and PI, and 371 data for LI. Based on the results, the IDW method gives reasonable predictions depending on the results of R2 and RMSE. The results also showed that the study area has relatively large zones of high expansive soil that must be taken into considerations before performing any construction activity. These maps are essential for helping geotechnical engineers in making decisions and visualizing soils’ behaviors.

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Publication Date
Sun Jan 01 2012
Journal Name
Indian Journal Of Dermatology
Lactic acid as a new therapeutic peeling agent in the treatment of lifa disease (frictional dermal melanosis)
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Publication Date
Wed Aug 30 2023
Journal Name
Baghdad Science Journal
Impact of COVID-19 Vaccine on Hearing Status of Young Ages (Medical College Students as a Sample)
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Many studies dealt with the consequences of  SARS CoV-2  (which cause COVID-19 infection) on the nervous system especially sensory nerves where the virus causes loss of taste and smell as it’s known, and may affect auditory nerves and be the expected cause of some hearing problems. A case-control analytic study was performed on a connivance sample of society of university students from a medical faculty. Each participant filled out a questionnaire contains demographic data and general, auditory and respiratory health condition, in addition to vaccination status. In the other side, the audio- examinations were performed on the study sample including Pure Tone Audiometry (PTA) and tympanometry. Two statistical methods; chi-square and t

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Publication Date
Thu Mar 03 2022
Journal Name
Archives Of Rheumatology
Association of tumor necrosis factor-alpha promoter region gene polymorphism at positions -308G/A, -857C/T, and -863C/A with etanercept response in Iraqi rheumatoid arthritis patients
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Objectives: This study aims to evaluate the association between polymorphisms in the promoter region of the tumor necrosis factor-alpha (TNF-α) gene at locations -308G/A, -857C/T, and -863C/A with the tendency of being non-responder to etanercept.

Patients and methods: Between October 2020 and August 2021, a total of 80 patients (10 males, 70 females; mean age: 50 years; range, 30 to 72 years) with rheumatoid arthritis (RA) receiving etanercept for at least six months were included. The patients were divided into two groups responders and non-responders, based on their response after six months of continuous treatment. Following polymerase chain reac

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Publication Date
Mon Jun 30 2014
Journal Name
Al-kindy College Medical Journal
Surgical variables analysis of 116 cases of ovarian cystic diseases in Al- Elwiya maternity teaching hospital at 2013
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Background: The treatment of an ovarian cyst relies on its nature, the discrimination of benign and malignant cysts is, therefore of crucial importance, and in spite of the continuous improvement of diagnostic means, it remains sometimes impossible to differentiate functional from organic (malignant or not) ovarian cysts. The therapeutic decision will search for the main midway between cancer’s negligence and the fear of performing an unnecessary surgical operation for an ovarian cyst.Objective: To review of 116 cases of ovarian cystic diseases aiming in identify proper management and reducing unnecessary surgical intervention.Methods: A retrospective study was conducted at Al-Elwiya maternity teaching hospital/ Baghdad/ Iraq. One hund

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Publication Date
Tue Dec 01 2020
Journal Name
Baghdad Science Journal
Detection of Suicidal Ideation on Twitter using Machine Learning & Ensemble Approaches
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Suicidal ideation is one of the most severe mental health issues faced by people all over the world. There are various risk factors involved that can lead to suicide. The most common & critical risk factors among them are depression, anxiety, social isolation and hopelessness. Early detection of these risk factors can help in preventing or reducing the number of suicides. Online social networking platforms like Twitter, Redditt and Facebook are becoming a new way for the people to express themselves freely without worrying about social stigma. This paper presents a methodology and experimentation using social media as a tool to analyse the suicidal ideation in a better way, thus helping in preventing the chances of being the victim o

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Publication Date
Tue May 01 2012
Journal Name
Iraqi Journal Of Physics
Detection of line shape parameters in normal and abnormal biological tissues
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Doppler broadening technique is suggested to monitor the development of tumours. It depends on the sensitivity of positronium (Ps) annihilation parameters to the sub- microstructural changes in biological tissues. This technique uses high resolution HpGe detector to measure the lineshape parameters (S and W) in normal mice's mammary tissues and adenocarcinoma mammary tissues as a function of tumour growth. The results demonstrate that the central parameter (S) decreases and the wing parameter (W) increases as the tumour grow. It is found that the S parameter changes considerably with the distribution of voids which are affected by the tumour development. Therefore the present technique can successfully be employed to monitor the developm

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Publication Date
Tue May 23 2023
Journal Name
Journal Of Engineering
Enhancement of the Detection of the TCP SYN Flooding (DDoS) Attack
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The major of DDoS attacks use TCP protocol and the TCP SYN flooding attack is the most common one among them. The SYN Cookie mechanism is used to defend against the TCP SYN flooding attack. It is an effective defense, but it has a disadvantage of high calculations and it doesn’t differentiate spoofed packets from legitimate packets. Therefore, filtering the spoofed packet can effectively enhance the SYN Cookie activity. Hop Count Filtering (HCF) is another mechanism used at the server side to filter spoofed packets. This mechanism has a drawback of being not a perfect and final solution in defending against the TCP SYN flooding attack. An enhanced mechanism of Integrating and combining the SYN Cookie with Hop Count Filtering (HCF) mech

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Publication Date
Wed Jun 24 2015
Journal Name
Chinese Journal Of Biomedical Engineering
Single Channel Fetal ECG Detection Using LMS and RLS Adaptive Filters
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ECG is an important tool for the primary diagnosis of heart diseases, which shows the electrophysiology of the heart. In our method, a single maternal abdominal ECG signal is taken as an input signal and the maternal P-QRS-T complexes of original signal is averaged and repeated and taken as a reference signal. LMS and RLS adaptive filters algorithms are applied. The results showed that the fetal ECGs have been successfully detected. The accuracy of Daisy database was up to 84% of LMS and 88% of RLS while PhysioNet was up to 98% and 96% for LMS and RLS respectively.

Publication Date
Mon Dec 14 2020
Journal Name
2020 13th International Conference On Developments In Esystems Engineering (dese)
Anomaly Based Intrusion Detection System Using Hierarchical Classification and Clustering Techniques
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With the rapid development of computers and network technologies, the security of information in the internet becomes compromise and many threats may affect the integrity of such information. Many researches are focused theirs works on providing solution to this threat. Machine learning and data mining are widely used in anomaly-detection schemes to decide whether or not a malicious activity is taking place on a network. In this paper a hierarchical classification for anomaly based intrusion detection system is proposed. Two levels of features selection and classification are used. In the first level, the global feature vector for detection the basic attacks (DoS, U2R, R2L and Probe) is selected. In the second level, four local feature vect

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Publication Date
Wed Nov 30 2022
Journal Name
Iraqi Journal Of Science
Breast Cancer Detection using Decision Tree and K-Nearest Neighbour Classifiers
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      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 minimu

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