Cognitive Schemas Have the Ability to Predict Emotional Schemas in Different Types of Anxiety Disorders
Issue:
Volume 2, Issue 6, December 2017
Pages:
120-126
Received:
15 October 2017
Accepted:
27 October 2017
Published:
18 December 2017
Abstract: Objective: This study intends to evaluate the Cognitive Schemas have the ability to predict Emotional schemas in different types of anxiety disorders. Method: The study was ex post facto (causal-comparative) is. 109 people suffering from anxiety disorders in six groups of panic disorder, without Through fear, social phobia, specific phobia, obsessive - compulsive disorder, post-traumatic stress and anxiety and acute stress that psychologists and psychiatrists (private and public centers) Tehran, referring and the random sampling method was applied. To evaluate the results of the tests of Young Schema and Leahy Schema, the variance analysis, Tukey and multivariate regression Questionnaire was used. The Cognitive Schemas have the ability to predict Emotional schemas in different types of anxiety disorders. Results: The results showed that, impaired performance (conversely), other-directedness and rejection/disconnection fields have the ability to predict emotional schema of controllability, rejection/disconnection and impaired limits had the ability to predict comprehensibility. The emotional schema of guilt could be predicted by the use of rejection/disconnection and other-directedness, over-vigilance-inhibition (conversely), other-directedness and rejection/disconnection (conversely) have the ability to explain emotional schema of higher values. Results indicate that emotional schema of duration could be predicted by over-vigilance-inhibition (conversely) and rejection/disconnection. Conclusions: In the model of emotional schema of controllability they have an obsessive desire to be under control by others, but this extreme fear of catastrophic events prevents them to trust to anybody. For the same, impaired performance (conversely) is able to determine emotional schema of consensus.
Abstract: Objective: This study intends to evaluate the Cognitive Schemas have the ability to predict Emotional schemas in different types of anxiety disorders. Method: The study was ex post facto (causal-comparative) is. 109 people suffering from anxiety disorders in six groups of panic disorder, without Through fear, social phobia, specific phobia, obsessi...
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Analysis on ECG Data Compression Using Wavelet Transform Technique
Hla Myo Tun,
Win Khaing Moe,
Zaw Min Naing
Issue:
Volume 2, Issue 6, December 2017
Pages:
127-140
Received:
8 October 2017
Accepted:
18 October 2017
Published:
22 December 2017
Abstract: Although digital storage media is not expensive and computational power has exponentially increased in past few years, the possibility of electrocardiogram (ECG) compression still attracts the attention, due to the huge amount of data that has to be stored and transmitted. ECG compression methods can be classified into two categories; direct method and transform method. A wide range of compression techniques were based on different transformation techniques. In this work, transform based signal compression is proposed. This method is used to exploit the redundancy in the signal. Wavelet based compression is evaluated to find an optimal compression strategy for ECG data compression. The algorithm for the one-dimensional case is modified and it is applied to compress ECG data. A wavelet ECG data code based on Run-length encoding compression algorithm is proposed in this research. Wavelet based compression algorithms for one-dimensional signals are presented along with the results of compression ECG data. Firstly, ECG signals are decomposed by discrete wavelet transform (DWT). The decomposed signals are compressed using thresholding and run-length encoding. Global and local thresholding are employed in the research. Different types of wavelets such as daubechies, haar, coiflets and symlets are applied for decomposition. Finally the compressed signal is reconstructed. Different types of wavelets are applied and their performances are evaluated in terms of compression ratio (CR), percent root mean square difference (PRD). Compression using HAAR wavelet and local thresholding are found to be optimal in terms of compression ratio.
Abstract: Although digital storage media is not expensive and computational power has exponentially increased in past few years, the possibility of electrocardiogram (ECG) compression still attracts the attention, due to the huge amount of data that has to be stored and transmitted. ECG compression methods can be classified into two categories; direct method...
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