Abstract
Disturbs the social system in any society specially in Iraq other than
other Islamic and Arabic countries. That is according to the abnormal
conditions that Iraq has past through as wars and blockage, and lastly the
invasion. Therefore it has been necessary to put this phenomenon under
study and analysis to discover Juvenile Delinquency is one of the most
prominent social phenomenon that the important reasons behind it, and trying
to treat what can be treated of the effects of it upon society.
This study is mainly concerned with the explaining the social factors
leading toward juvenile delinquency trying to crystallize the problem of the
study in the following question: (What are the psychological, social,
economical factors leading toward juvenile delinquency?)
The study aims at recognizing the order of the different factors of
juvenile delinquency and knowing the effect of the social factors on it, in
addition to the family factors affecting the delinquency.
The importance of the study comes from the importance of the
phenomenon itself. The study identifies the social factors resulting in the
delinquency of the juvenile. It is important, for it shows the main family factors
in all its different sides resulting in the behaviour of the juvenile. The study
tries to put the scales to treat the phenomenon.
In its theoretical frame, the study has discussed the phenomenon of
juvenile delinquency and the factors behind it.
The researcher has showed several former studies in the same field
that have focused on the most important factors affecting the appearance of
the phenomenon.
Analyzing plantar pressure trajectories is crucial for assessing foot behavior in dynamic gait stability. We propose the identification of foot symmetry and the detection of deformities by analyzing the trajectories of the center of pressure (CoP) and peak pressure (PP). First, using a foot pressure mapping system, plantar pressure data are acquired during a normal gait cycle. After the data have been acquired, post processing extracts both the CoP and PP trajectories over the spatiotemporal domain of foot motion for each foot independently. For this purpose, we used the optical flow technique which accurately estimates the direction of foot motion. The extracted trajectories of each foot are then segmented into, the medial and lateral regi
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Modern statistical techniques offer a range of methodologies for modelling time series data, with conditional and unconditional approaches providing complementary insights that enhance overall model accuracy. This article introduced a modified ARIMA model employing conditional and unconditional parameter estimates. The methodology for the new model based on novel methods is provided. The prediction process, one and two steps ahead, is covered in detail, and a novel algorithm is presented. The best model is picked based on various measurement criteria, such as coefficient of determination (R2), root mean squared error (RMSE), and mean absolute scaled error (MASE). The suggested model is applied to a monthly petrol sales dataset (Jan
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