Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3

relaxation Related Publications

3 Influence of Boron Doping and Thermal Treatment on Internal Friction of Monocrystalline Si1-xGex(x≤0,02) Alloys

Authors: I. Kurashvili, A. Sichinava, G. Bokuchava, G. Darsavelidze, I. Tabatadze

Abstract:

The impact of boron doping on the internal friction (IF) and shear modulus temperature spectra of Si1-xGex(x≤0,02) monocrsytals has been investigated by reverse torsional pendulum oscillations characteristics testing. At room temperatures, microhardness and indentation modulus of the same specimens have been measured by dynamic ultra microhardness tester. It is shown that boron doping causes two kinds effect: At low boron concentration (~1015 cm-3) significant strengthening is revealed, while at the high boron concentration (~1019 cm-3) strengthening effect and activation characteristics of relaxation origin IF processes are reduced.

Keywords: relaxation, Microhardness, internal friction, dislocation

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2 Identification of Arousal and Relaxation by using SVM-Based Fusion of PPG Features

Authors: Chi Jung Kim, Mincheol Whang, Eui Chul Lee

Abstract:

In this paper, we propose a new method to distinguish between arousal and relaxation states by using multiple features acquired from a photoplethysmogram (PPG) and support vector machine (SVM). To induce arousal and relaxation states in subjects, 2 kinds of sound stimuli are used, and their corresponding biosignals are obtained using the PPG sensor. Two features–pulse to pulse interval (PPI) and pulse amplitude (PA)–are extracted from acquired PPG data, and a nonlinear classification between arousal and relaxation is performed using SVM. This methodology has several advantages when compared with previous similar studies. Firstly, we extracted 2 separate features from PPG, i.e., PPI and PA. Secondly, in order to improve the classification accuracy, SVM-based nonlinear classification was performed. Thirdly, to solve classification problems caused by generalized features of whole subjects, we defined each threshold according to individual features. Experimental results showed that the average classification accuracy was 74.67%. Also, the proposed method showed the better identification performance than the single feature based methods. From this result, we confirmed that arousal and relaxation can be classified using SVM and PPG features.

Keywords: Emotion recognition, relaxation, arousal, support vector machine, PPG

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1 The Effect of Relaxation Training on First Year Nursing Students Anxiety in Clinical Setting

Authors: S. Ahmadnejad, Z. Monjamed, M. Pakravannejad, A. Malekian

Abstract:

The investigating and assessing the effects of relaxation training on the levels of state anxiety concerning first year female nursing students at their initial experience in clinical setting. This research is a quasi experimental study that was carried out in nursing and midwifery faculty of Tehran university of medical sciences .The sample of research consists 60 first term female nursing students were selected through convenience and random sampling. 30 of them were the experimental group and 30 of them were in control group. The Instruments of data-collection has been a questionnaire which consists of 3 parts. The first part includes 10 questions about demographic characteristics .the second part includes 20 question about anxiety (test 'Spielberg' ). The 3rd part includes physiological indicators of anxiety (BP, P, R, body temperature). The statistical tests included t-test and  and fisher test, Data were analyzed by SPSS software.

Keywords: Anxiety, relaxation, nursing students

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