International Journal of Recent Advances in Science and Technology 2020-05-31T14:16:58-04:00 Yogesh Kumar Open Journal Systems Review on Learning System for Detecting Transformer Internal Faults 2020-05-15T14:26:34-04:00 Kumar Shri Ram Ankush Sood Priya Sharma Navdeep Singh <p>Miniature transformer is one of the most important components of electronic devices. A serious failure of such kind of transformer may cause loss of time and money. This paper presents a learning system to recognize internal fault of such kind of transformer. The different kinds of faults are made to occur intentionally and data are collected at various conditions. The faults include turn to turn, winding to ground, and dielectric faults. The data are then processed and entered in the learning algorithms to recognize the type of fault. We devise a learning system to recognize the various types of faults. Several versions of learning algorithms such as standard back propagation, Levenberg-Marquardt, Bayesian regulation, Resilient back propagation, Gradient descent, One-step secant, Elman recurrent network are used. The result of Levenberg-Marquardt algorithm was found to be faster than that of other algorithms. Therefore it is suitable for real time fault detection.</p> 2019-09-30T00:00:00-04:00 Copyright (c) 2020 Determining the Effect of Using the Fordyce Joy Pattern on Stress Anxiety and Depression of Diabetics in the Selected Hospitals of the Faculty of Medical Sciences of Abadan 2020-05-23T12:14:35-04:00 Samaneh Naeimi Soheila Beigi Masoud Torabpour Shilan Azizi Elham Merdasi <p><strong>Background and Aims:</strong> Diabetes is one of the most common metabolic diseases with debilitating effects, with a chronic and imperceptible course, and is on the rise, and is a source of stress for people with the disease. In addition to the physical effects of diabetes, stress also has a negative psychological effect, the most important of which is depression. Therefore, the aim of this study was to investigate the effect of using Fordyce happiness pattern on stress, anxiety, and depression in diabetic patients.</p> <p><strong>Method:</strong> The present study was a two-group intervention study in two stages before and immediately after the intervention, which was performed on 50 patients with diabetes hospitalized in Abadan educational and medical hospitals in 2019. Samples were randomly selected and then randomly divided into intervention and control groups. Happiness training was given to patients in 3 sessions by the researcher and to collect data, a 21-item DASS questionnaire was used as a pre-test and post-test in both groups.</p> <p><strong>Results:</strong> The results of independent t-test showed that the mean stress, anxiety, and depression before the intervention were not significantly different between the two groups (p&gt; 0.05) but in the intervention group between the two groups were statistically different (p &lt;0.05). Intragroup comparisons also showed that the mean stress, anxiety, and depression in the control group after the intervention did not have a statistically significant difference (p &lt;0.05) but in the test group after the intervention there was a statistically significant difference (p &lt;0.05).</p> <p><strong>Conclusion:</strong> The results indicate the effectiveness of Forday's happiness model on the level of anxiety, stress, and depression of diabetic patients, so it is recommended that this model be used as a suitable guide and solution in clinics and diabetes centers.</p> 2019-09-30T00:00:00-04:00 Copyright (c) 2020