The study's primary purpose is to explore an appropriate way of monitoring and assessing water depths using the satellite remote sensing technique of the Al Habbaniyah Lake in Iraq. This research studied the experience-conditions (thresholds) of different bands for multi-temporal satellite image data with different satellite image sensors (Landsat 5-TM, and EO1-ALI) for the same region, to recognize regions of water depths. The threshold values are taken that to separate the Al Habbaniyah Lake to the required depths (shallow, deep, and very deep), as a supervised method. A three-dimension feature space plot had used to represent these regions. The relationship of the mean values of the three separated water regions with all TM and A
... Show MorePsi prepared by Electrochemical etching technique at invariable etching current density of 10 mA/cm2 and at different times (7 and 17) min. The porous Si structure was studied using XRD, (FE-SEM) and EDS. The process of sensing NH3 gas is carried out at different operating temperatures (R.t,80,130 and 200)°C and the gas concentration is constant. It is measured by changing the resistance of the sensor as a function of exposure time to the gas. The result showed the XRD patterns of the PS at (7 and 17) min etching time. the peak samples at (111) around 2θ = 28.5°. It is observed that the peak intensity declines with rising the etching time,
Groundwater is an important source of fresh water especially in countries having a decrease in or no surface water; therefore itis essential to assess the quality of groundwater and find the possibility of its use in different purposes (domestic; agricultural; animal; and other purposes). In this paper samples from 66 wells lying in different places in Baghdad city were used to determine 13 water parameters, to find the quality of groundwater and evaluate the possibility of using it for human, animal and irrigation by calculating WQI, SAR, RSC and Na% and TDS indicators. WQI results showed that the groundwater in all wells are not qualified for human use, while SAR and RSC indicated that most samples are suitable for irrigation use, and
... Show MoreLK Abood, RA Ali, M Maliki, International Journal of Science and Research, 2015 - Cited by 2
Abstract—The upper limb amputation exerts a significant burden on the amputee, limiting their ability to perform everyday activities, and degrading their quality of life. Amputee patients’ quality of life can be improved if they have natural control over their prosthetic hands. Among the biological signals, most commonly used to predict upper limb motor intentions, surface electromyography (sEMG), and axial acceleration sensor signals are essential components of shoulder-level upper limb prosthetic hand control systems. In this work, a pattern recognition system is proposed to create a plan for categorizing high-level upper limb prostheses in seven various types of shoulder girdle motions. Thus, combining seven feature groups, w
... Show MoreRA Ali, LK Abood, Int J Sci Res, 2017 - Cited by 2
Recently, the development of the field of biomedical engineering has led to a renewed interest in detection of several events. In this paper a new approach used to detect specific parameter and relations between three biomedical signals that used in clinical diagnosis. These include the phonocardiography (PCG), electrocardiography (ECG) and photoplethysmography (PPG) or sometimes it called the carotid pulse related to the position of electrode.
Comparisons between three cases (two normal cases and one abnormal case) are used to indicate the delay that may occurred due to the deficiency of the cardiac muscle or valve in an abnormal case.
The results shown that S1 and S2, first and second sound of the
... Show MoreCOVID 19 has spread rapidly around the world due to the lack of a suitable vaccine; therefore the early prediction of those infected with this virus is extremely important attempting to control it by quarantining the infected people and giving them possible medical attention to limit its spread. This work suggests a model for predicting the COVID 19 virus using feature selection techniques. The proposed model consists of three stages which include the preprocessing stage, the features selection stage, and the classification stage. This work uses a data set consists of 8571 records, with forty features for patients from different countries. Two feature selection techniques are used in