Recently there has been an urgent need to identify the ages from their personal pictures and to be used in the field of security of personal and biometric, interaction between human and computer, security of information, law enforcement. However, in spite of advances in age estimation, it stills a difficult problem. This is because the face old age process is determined not only by radical factors, e.g. genetic factors, but also by external factors, e.g. lifestyle, expression, and environment. This paper utilized machine learning technique to intelligent age estimation from facial images using support vector machine (SVM) on FG_NET dataset. The proposed work consists of three phases: the first phase is image preprocessing include four stages: grayscale image stage, histogram equalization stage, face detection stage has been carried out using viola jones algorithm, it comprises for four steps namely: Haar like Feature, integral image, Adaboost training, and cascading classifier, the last stage of image preprocessing phase is cropping and resize stage. The second phase is data mining include two stages: feature extraction stage using linear discriminate analysis and machine learning stage using support vector machine. The last phase is age estimation and evaluation. The FG-net dataset is used which divided into seven classes in order to has been became increased accuracy and reduce the execution time, the first class represents 3-7 years, the second class represents 8-13 years, the third class represents 14-19 years, the forth class represents 20-25 years, the fifth class represents 26-30 years, the sixth class represents 31-40 years and the seven class represents 41-50 years. Then, the seven classes are combined into three classes depending on the number of features. The Experimental results display that the proposed system can grant high accuracy. The practical evaluation of the proposed system gives accuracy is 84%.
Age Estimation Using Support Vector Machine
Viola jones
linear discriminate analysis
machine earning
SVM classifier
Age estimation
Publication Date
Tue Mar 01 2022
Journal Name
Iraqi Journal Of Agricultural Sciences
CORRELATION OF TMPRSS2-ERG GENE FUSION STATUS WITH CLINICOPATHOLOGICAL CHARACTERISTICS IN PROSTATE CANCER OF IRAQI PATIENTS
The aim of this study was to establish the existence and interaction of TMPRSS2 – ERG gene fusion status with clinicopathological features of prostate cancer patients. This research consisted of 123 embedded formalin-fixed tissues obtained from the prostate tumor patients. The above gene fusion is detected through the technique of fluorescent in situ hybridization (FISH) by means of a triple color probe. Seven samples have not been scored due to technical difficulties and 46 patients have fusion (39.6%)
while the remaining (70) have not been seen with fusion. Of the 46 fusion-positive
17 (36%) were caused by ERG-translocation
of the other 29 (63%) were caused by the interstitial segment deletion between the two genes due to their sequential position. In order to find a substantial correlation between 116 patients (fusion took place in 46 and non-fusion in 70) with clinicopathological features
the following findings were calculated: Our findings recorded non-significant correlation at age
BMI and tumor size at which (P-value >0.05).While results showed significant association with: pathological T stage (P value = 0.011)
Gleason score (P value = 0.002)
perineural invasion (P value = 0.047) and PSA (P value = 0.033). The clinicopathological features which had a considerable correlation with fusion status are very important as they aid the doctors in prognosis and treatment of such tumor.
Publication Date
Tue Apr 01 2014
Journal Name
Journal Of Economics And Administrative Sciences
Financial markets liquidity and their impact in the return of common stocks
The research aimed to study the financial markets liquidity and returns of common stocks
Take the research the theoretical concepts associated with each of the liquidity of financial markets and returns of common stocks
As well as the use of mathematical methods in the practical side to measure market liquidity and Stocks Return
the community of research in listed companies in Iraqi stock exchange that have been trading on its stock and number 85 joint-stock company
The research was based to one premise
there is a statistically significant effect for the liquidity of the Iraqi stock exchange on returns of common stocks to traded companies in which
Using the SPSS program was to test the hypothesis research population represented Iraq Stock Exchange for a period of three years (2010-2012) on a monthly basis. The research found the set of conclusions most important rising market liquidity for Iraq Stock Exchange and followed increase in return of common stocks for a period of research
as the results of statistical analysis indicated the presence of a statistically significant effect of moral Iraq Stock Exchange liquidity on returns of common stocks
and most important recommendations should the Iraq Stock Exchange work to expand its activities in electronic trading
by providing the possibility of trading for investors through the Internet
and not limited to trading within the market
and should work to reduce the transaction costs to raise the liquidity common stock
and thus reflect positively on the liquidity of the Iraq Stock Exchange brokerage firms associated with it .
The research aimed to study the financial markets liquidity and returns of common stocks , Take the research the theoretical concepts associated with each of the liquidity of financial markets and returns of common stocks , As well as the use of mathematical methods in the practical side to measure market liquidity and Stocks Return, the community of research in listed companies in Iraqi stock exchange that have been trading on its stock and number 85 joint-stock company, The research was based to one premise, there is a statistically significant effect for the liquidity of the Iraqi stock exchange on returns of common stocks to traded companies in which , Using th
... Show More