An in-depth experimental study of the matrix effect of antifreeze (ethylene glycol) and water contamination of engine oil through FT-IR spectroscopy. With a comparison of the percent by volume concentration of contaminated fresh 15W-40 engine oil, there appeared to be a noticeable reduction in the O–H stretching signal in the infrared spectrum when ethylene glycol based antifreeze was included as a contaminant. The contaminants of distilled water, a 50/50 mixture of water and commercial ethylene glycol antifreeze, and straight ethylene glycol antifreeze were compared and a signal reduction in the O–H stretch was clearly evident when glycol was present. Doubling the volume of the 50/50 mixture as compared to water alone still res

The aim of the research is to identify the suitability of a patrol model in evaluating the financial performance of Iraqi banks. The financial reports of five Iraqi commercial banks were approved as a sample for research for the period from 2015 to 2020. The most common financial ratios were adopted for the purpose of measuring the five elements of the model, which are capital adequacy, profitability, credit risk, bankal efficiency and liquidity. The results showed the possibility of using the PATROL model in evaluating the performance of Iraqi banks, as it gave a realistic image of the reality of Iraqi banks in terms of high capital adequacy index and high liquidity, as well as fluctuation in profitability index, not to mention the prob

Dry environment study forms an important part in the field of applies geomorphology for
the wide rang of its lands which form most of the world, homeland, and Iraqi lands specially,
and what these lands include of scientific cases which needs to be searched and investigated.
They include rocks, land shapes, water supplements, its ancient soil and its active diggings are
all signs of the environment changes and effects that these lands under take over time, with
continuous remains of its features of characteristics under geo morphological dry
circumstances which works to slow change average, when the geomorphologic fearers varies
in this environment and what it contain of important economical resource. As to participl

In this paper, integrated quantum neural network (QNN), which is a class of feedforward

neural networks (FFNN’s), is performed through emerging quantum computing (QC) with artificial neural network(ANN) classifier. It is used in data classification technique, and here iris flower data is used as a classification signals. For this purpose independent component analysis (ICA) is used as a feature extraction technique after normalization of these signals, the architecture of (QNN’s) has inherently built in fuzzy, hidden units of these networks (QNN’s) to develop quantized representations of sample information provided by the training data set in various graded levels of certainty. Experimental results presented here show that

Audio classification is the process to classify different audio types according to contents. It is implemented in a large variety of real world problems, all classification applications allowed the target subjects to be viewed as a specific type of audio and hence, there is a variety in the audio types and every type has to be treatedcarefully according to its significant properties.Feature extraction is an important process for audio classification. This workintroduces several sets of features according to the type, two types of audio (datasets) were studied. Two different features sets are proposed: (i) firstorder gradient feature vector, and (ii) Local roughness feature vector, the experimentsshowed that the results are competitive to

In every country in the world, there are a number of amputees who have been exposed to some accidents that led to the loss of their upper limbs. The aim of this study is to suggest a system for real-time classification of five classes of shoulder girdle motions for high-level upper limb amputees using a pattern recognition system. In the suggested system, the wavelet transform was utilized for feature extraction, and the extreme learning machine was used as a classifier. The system was tested on four intact-limbed subjects and one amputee, with eight channels involving five electromyography channels and three-axis accelerometer sensor. The study shows that the suggested pattern recognition system has the ability to classify the sho

This abstract focuses on the significance of wireless body area networks (WBANs) as a cutting-edge and self-governing technology, which has garnered substantial attention from researchers. The central challenge faced by WBANs revolves around upholding quality of service (QoS) within rapidly evolving sectors like healthcare. The intricate task of managing diverse traffic types with limited resources further compounds this challenge. Particularly in medical WBANs, the prioritization of vital data is crucial to ensure prompt delivery of critical information. Given the stringent requirements of these systems, any data loss or delays are untenable, necessitating the implementation of intelligent algorithms. These algorithms play a pivota