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Self-determintion and Emotional Experience and their Relationship with achievement striving for the college Students
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Human beings have an innate and natural aim to achieve their self-interests and to show their ability to overcome challenges in a better way, therefore the move towards self determination is expressed by intrinsic motivation. The desire of absorbing in this task is to enjoy the task in it self and benefitting from it such a motivation is the desire rooted in human nature to judge and choose in which individual is conscious in his self, abilities and adequacy that help him in control the different  situations of life passed by him. His choices and actions are voluntary  and non-restricted to intervention or external control because control is inner and subjective, while his behavior is self-regulated with the feeling of independence, that is the feeling of psychological freedom and the motivation of self-determination. with this independence, human being enjoys power and psychological health as they are necessary for health , integration and  happiness. Self –determination is regarded as humane , civilized and social phenomenom whose association indicating positively self-wellbeing , general health, creativity and achievement  in most fields of active life. The importance of self-determination required its study and acquainting with it and the emotional experience and their relationship with achievement striving.

The present research aims to:

  1. Acquainting with self-determination for the college students.
  2. Acquainting with emotional experience for the college students.
  3. Acquainting with achievement striving for the college students.
  4. Acquainting with the significance differences in self-determination for the college students according to two variables : gender “males, females” and major “scientific,humanistic”
  5. Acquainting with the significant differences in emotional experience for the college students according to two variables :gender “males, females” and major “scientific , humanistic”
  6. Acquainting with the significant differences in achievement striving for the college students according to two variables : gender “males, females “ major “scientific , humanistic”
  7. The extent of contribution of self-determination and emotional experience in total variance of achievement striving for the college students.

To achieve the research aims, the researcher built three scales for the present research and verified their valdity and analysed their items statistically on a sample consisting of 600 male and female college students to find discriminate power and validity for their  items.

The reliability of scales was computed by the re-test way and cronbach’s  alpha.

After completing of scales ‘ building , they were applied on the researcher’s main sample

‘400 male and female students” . having collected the data and processed them statistically, the researcher reached several findings , the most important of them as follows:

  1. The mean of self-determination degrees for the research sample was higher than the hypothetical mean and that indicates that sample subjects have high self-determination.
  2. The mean of emotional experience degrees for the sample was higher than the hypothetical mean and that indicates that sample subjects have high emotional experience.
  3. The mean of achievement striving degrees was higher than the sample have high motivation for achievement  striving .

In the light of these findings and as completion for the fields associated with the present  resarch, and the researcher recommended several of recommends as she suggested conducting several scientific studies and researches.

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Publication Date
Mon Nov 21 2022
Journal Name
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Deep Learning-Based Computer-Aided Diagnosis (CAD): Applications for Medical Image Datasets
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Computer-aided diagnosis (CAD) has proved to be an effective and accurate method for diagnostic prediction over the years. This article focuses on the development of an automated CAD system with the intent to perform diagnosis as accurately as possible. Deep learning methods have been able to produce impressive results on medical image datasets. This study employs deep learning methods in conjunction with meta-heuristic algorithms and supervised machine-learning algorithms to perform an accurate diagnosis. Pre-trained convolutional neural networks (CNNs) or auto-encoder are used for feature extraction, whereas feature selection is performed using an ant colony optimization (ACO) algorithm. Ant colony optimization helps to search for the bes

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Various Extracts of Some Medicinal Plants as Inhibitors for Beta-lactamase Activity
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The inhibitory effect of acetone, ethanol, and aqueous extracts of ten medicinal plants on β-lactamase from Staphylococcus sciuri and Klebsiella pneumoniae was investigated in vitro by starch-iodine agar plate method. The results revealed the success of starch-iodine method for the detection of the inhibition of β-lactamase activity by the various extracts of each individual plant. The acetone extracts of Catharanthus roseus, Eucalyptus camaldulensis, and Schinus terebinthifolius induced an inhibitory effect on β-lactamase from Staphylococcus sciuri. On the other hand, acetone extracts from only Eucalyptus camaldulensis, and Schinus

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Publication Date
Tue Jun 15 2021
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Recently emerging pandemic SARS CoV-2 conquered our world since December 2019. Continuous efforts have been done to find out effective immunization and precise treatment stetratigies A way from therapeutic options that were tried in SARS CoV-2, an increased attention is directed to predict natural products and mainly phytochemicals as collaborative measures for this crisis. In this review, most of the mentioned compounds specially flavonoids (biacalin, hesperidin, quercetin, luteolin,, and phenolic (resveratrol, curcumin, and theaflavin) exert their effect through interfering with the action of one or more of this proteins (spike protein, papain like protease, 3 chymotrypsin like cysteine protease, and RNA dependent RNA 

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Publication Date
Sun Mar 28 2021
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A Light Weight Multi-Objective Task Offloading Optimization for Vehicular Fog Computing
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Most Internet of Vehicles (IoV) applications are delay-sensitive and require resources for data storage and tasks processing, which is very difficult to afford by vehicles. Such tasks are often offloaded to more powerful entities, like cloud and fog servers. Fog computing is decentralized infrastructure located between data source and cloud, supplies several benefits that make it a non-frivolous extension of the cloud. The high volume data which is generated by vehicles’ sensors and also the limited computation capabilities of vehicles have imposed several challenges on VANETs systems. Therefore, VANETs is integrated with fog computing to form a paradigm namely Vehicular Fog Computing (VFC) which provide low-latency services to mo

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Publication Date
Mon Jun 09 2025
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A novel improvement of skew tent map for generating Pseudo random numbers
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An encryption system needs unpredictability and randomness property to maintain information security during transmission and storage. Although chaotic maps have this property, they have limitations such as low Lyapunov exponents, low sensitivity and limited chaotic regions. The paper presents a new improved skewed tent map to address these problems. The improved skew tent map (ISTM) increases the sensitivity to initial conditions and control parameters. It has uniform distribution of output sequences. The programs for ISTM chaotic behavior were implemented in MATLAB R2023b. The novel ISTM produces a binary sequence, with high degree of complexity and good randomness properties. The performance of the ISTM generator shows effective s

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