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Open Access Article
1 - An analytic algorithm of Lane-Emden-type equations arising in astrophysics - a hybrid approach
Vipul K Baranwal Ram K Pandey Manoj P Tripathi Om P Singh -
Open Access Article
2 - Application of the exact operational matrices for solving the Emden-Fowler equations, arising in Astrophysics
S. A. Hossayni‎ J. A. Rad K. Parand S. Abbasbandy -
Open Access Article
3 - Solving nonlinear Lane-Emden type equations with unsupervised combined artificial neural networks
K. Parand Z. Roozbahani F. Bayat Babolghani -
Open Access Article
4 - The Effectiveness of Eye Movement Desensitization and Reprocessing Technique on Chronic Post-traumatic Stress Disorder (PTSD) In Soldiers
علیرضا ماردپور فرح نادری مهناز مهرابیزاده هنرمند Hassan Ahadi Alireza HeydariThis study aimed to examine the effectiveness of eye movement desensitization and reprocessing (EMDR) technique on soldiers' chronic post-traumatic stress disorder (PTSD). The population was all soldiers with PTSD psychiatric records in the Salman hospital of Yasooj. Fr MoreThis study aimed to examine the effectiveness of eye movement desensitization and reprocessing (EMDR) technique on soldiers' chronic post-traumatic stress disorder (PTSD). The population was all soldiers with PTSD psychiatric records in the Salman hospital of Yasooj. From this population 32 persons were selected through simple random sampling and assigned into two experimental and control groups (each group, 16 persons). The experimental group received EMDR training for 5 sessions, 90 minutes each once a week but control group received no training. The study instruments included Impact of Event Scale-Revised, PTSD symptoms self-report scale, Beck Anxiety Inventory and Beck Depression Inventory. Subjective Units of Distress, and Validity of Cognition scales. Participants were tested at pre-test, post-test, and a three-month follow up stages. Data were analysed using MANCOVA and ANCOVA methods. Findings showed that the method of EMDR decreases the means of Impact of Event Scale-Revised, PTSD Symptoms Self-report Scale, Beck Anxiety Inventory and Beck Depression Inventory (P=0.001).The follow up findings also revealed that there are significant differences between the control and the experimental groups in the variables under study (P=0.001). The Findings suggested that this method is effective in alleviating PTSD and its symptoms. Manuscript profile -
Open Access Article
5 - Differential Information Extraction of Electroencephalogram Signals for Obsessive-Compulsive Disorder Detection
Farzaneh Manzari Peyvand GhaderyanIntroduction: Obsessive-Compulsive Disorder (OCD) is a chronic mental and social disease that is prevalent in about 2 to 3% of the human population leading to cognitive impairments and affected quality of patient's life. Therefore, a reliable and timely diagnosis can he MoreIntroduction: Obsessive-Compulsive Disorder (OCD) is a chronic mental and social disease that is prevalent in about 2 to 3% of the human population leading to cognitive impairments and affected quality of patient's life. Therefore, a reliable and timely diagnosis can help psychiatrists in better treating or controlling this disease.Method: Previous studies have demonstrated interdependence impairments between different brain regions in patients with OCD. Hence, this study has provided a new approach based on the decomposition of signals into intrinsic components and extraction of differential transient changes in amplitude envelope and phase spectra of the EEG signal recorded during Flanker tasks. The proposed algorithm has been evaluated using 19 healthy subjects and 11 patients by the Support Vector Machine (SVM) classifier.Result: The obtained results have confirmed the capability of the proposed method in diagnosing the disease with high accuracy of 93.89% using amplitude differential information of the electroencephalogram signal.Conclusion: In comparison between different regions, the statistical features extracted from the frontal lobe, the frontal-parietal network, and the inter-hemispheric features have offered better detection ability. Manuscript profile -
Open Access Article
6 - Throughput Improvement of RIPEMD-160 Design using Unfolding Transformation Technique
Shamsiah binti Suhaili Takahiro Watanabe Norhuzaimin Julai -
Open Access Article
7 - A Comparative Simulation Study of Nonlinear Time Series Model for Forecasting Tourism Data
Rafidah ALI -
Open Access Article
8 - Classification and Feature Extraction of Electroencephalogram Signals for Epilepsy Using PCA, ICA, DWT and SVM Methods
Javad Ebrahimnejad Mahkam Kahkesh Alireza NaghshThe purpose of this article is to classify electroencephalogram signals into two types of epilepsy and healthy.To achieve the highest accuracy, various techniques have been used. The desired characteristics of these signals can be extracted by Wavelet Transform and Empi MoreThe purpose of this article is to classify electroencephalogram signals into two types of epilepsy and healthy.To achieve the highest accuracy, various techniques have been used. The desired characteristics of these signals can be extracted by Wavelet Transform and Empirical Mode Decomposition methods.These two methods are compared in terms of impact in the classification process. To reduce the dimensions of the feature space, Independent and principal Component Analysis methods can be used. Then, in order to reduce the effect of noise on electroencephalogram signal analysis, a smoothing method can be applied.Finally, by using Support Vector machine classifier, the existing data classified.These steps were tested for an existing data set, including 5 groups of single channel electroencephalogram signals. Results show that the empirical decomposition method has high efficiency and accuracy to extract the characteristics and classification of signals. Accordingly, the accuracy and sensitivity of both combinations of "empirical mode decomposition - independent component analysis" and "empirical mode decomposition - principal component analysis", after data smoothing, as a new approach to extraction and classification of features are 100%. The output of this system is used to control and treat the disease. Manuscript profile -
Open Access Article
9 - New Strategy for Stopping Sifting Process during Bio-signals De-nosing By EMD: In Case of Low Frequency Artifact Reduction from ECG and EMG
Mohammad Shahbakhti Elnaz Heydari Mohsen Naji -
Open Access Article
10 - Identification and frequency of most important Tomato viruses in Bushehr province
Abbas Sharzei Sara Heidary Leila Shahbazi Fariba Raoufi Zahra MohandesyBackground & Objectives: Bushehr province is one of the major out of season tomato growing centres in Iran. The present study aimed to identify the most important tomato viruses and to determine their frequency following observation of the massive damages in these f MoreBackground & Objectives: Bushehr province is one of the major out of season tomato growing centres in Iran. The present study aimed to identify the most important tomato viruses and to determine their frequency following observation of the massive damages in these farms. Materials & Methods: This cross-sectional study was conducted on 250 tomato samples collected from fields in Bushehr province, which showed signs of leaf mosaic, vein clearing, mottling, and stunting. The samples were tested by DAS-ELISA using polyclonal antibodies against major known tomato viruses to identify the viruses. Results: The results showed that tomato fields were infected with Tomato yellow leaf curl virus (TYLCV), Zucchini yellow mosaic virus (ZYMV), Eggplant mottled dwarf virus (EMDV), Cucumber mosaic virus (CMV), Alfalfa mosaic virus (AMV), Potato virus X (PVX) and Tomato mosaic virus (ToMV) with a frequency of 94.5, 72, 65, 56.7, 27, 5.4 and 5%, respectively. No infections were observed with Squash mosaic virus (SMV), Potato virus Y (PVY), Watermelon mosaic virus (WMV) and Potato leaf roll virus (PLRV). Conclusion: The results of this study showed highly contamination (50-95%) of these fields to TYLCV, ZYMV, EMDV and CMV. Therefore, application of precautionary operations, especially at the level of purchasing the spores and tracking the sings of diseases and vector insects, looks necessary to control the distribution of these viruses. Manuscript profile -
Open Access Article
11 - Presenting the Forecasting Model of Bitcoin Return Using the hybrid Method of Deep Learning - Signal Decomposition Algorithm (CEEMD-DL)
sakineh sayyadi nezhad Ali Esmaeil Zadeh Mohammad Reza RostamiAbstract With the increasing popularity and widespread use of cryptocurrencies, the creation and development of methods for predicting price movements in this field has attracted a lot of attention. In between, recent developments in deep learning (DL) models with stru MoreAbstract With the increasing popularity and widespread use of cryptocurrencies, the creation and development of methods for predicting price movements in this field has attracted a lot of attention. In between, recent developments in deep learning (DL) models with structures such as long-short-term memory (LSTM) and convolutional neural network (CNN) have made improvements in the analysis of this type of data. Another approach that can be effective in the analysis of cryptocurrencies time series is the decomposition through algorithms such as complete integrated empirical mode decomposition (CEEMD). Considering the importance of forecasting in the cryptocurrencies field, in this research, by combining deep learning models and complete integrated empirical mode decomposition (CEEMD), The hybrid CEEMD-DL(LSTM) model has been used to forecast the bitcoin return (as the most popular currency). In this regard, the daily data of the total index of the Tehran Stock Exchange was used in the period of 2013/01/01 – 2022/05/28 and the results obtained were compared with the results of competing models based on efficiency measurement criteria. Based on the obtained results, the use of the introduced model (CEEMD-DL(LSTM)) has increased the efficiency and accuracy of bitcoin return forecasting. Accordingly, the use of this model in this field is suggested. Manuscript profile -
Open Access Article
12 - Using Reproducing Kernel for Solving the Lane-Emden Equations, Arising in Astrophysics
Ebrahim Amini Asghar Taheri Majid Abedini -
Open Access Article
13 - Numerical Solution of the Lane-Emden Equation Based on DE Transformation via Sinc Collocation Method
Ghasem Kazemi Gelian