Background; paraphilias were studied in the sex
clinic, at Al-Rashad teaching mental hospital, in the
years 2009-2010, a subject never touched before in the
field of psychiatry in Iraq.
Aims of the study :
1-to identify the prevalence of types and number of
paraphilias in those patients.
2-to study the relationship of paraphilias with
sociodemographic factors of the patients.
Patients and methods; using the diagnostic criteria of
DSM IV TR, 52 patients from the outpatient sex clinic
at Al-Rashad mental hospital, collected and studied (41
males and 11 females).
Results; the ratio of men to women was 3.7 : 1, the
majority of our sample was in the age range of 21-30
years (36.35%), with a limited(primary education)(
about 48%) or no education(36.53%), not married as a
status was found in 48.07%, and low socio-economic
level was in 57.69% of our sample. Exhibitionism was
found in 19.23% of our sample, followed by zoophilia
in males 17.07%, most of the disorders were found
exclusively in males, apart from masochism and some
of the paraphilias not otherwise specified (NOS).
Conclusion; paraphilia as a group of disorders, exist in
our society, but lurks in the shadows of our strict
cultural and religious societal background, they are
suppressed and stigmatized, for the majority of our
patients were collected first in a private clinic, then
directed and encouraged to the sex clinic by the
researchers.
These days, it is crucial to discern between different types of human behavior, and artificial intelligence techniques play a big part in that. The characteristics of the feedforward artificial neural network (FANN) algorithm and the genetic algorithm have been combined to create an important working mechanism that aids in this field. The proposed system can be used for essential tasks in life, such as analysis, automation, control, recognition, and other tasks. Crossover and mutation are the two primary mechanisms used by the genetic algorithm in the proposed system to replace the back propagation process in ANN. While the feedforward artificial neural network technique is focused on input processing, this should be based on the proce
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