Mohamed Yacin Sikkandar | University of Majmaah (original) (raw)
Papers by Mohamed Yacin Sikkandar
PeerJ
Purpose Insomnia-related affective functional disorder may negatively affect social cognition suc... more Purpose Insomnia-related affective functional disorder may negatively affect social cognition such as empathy, altruism, and attitude toward providing care. No previous studies have ever investigated the mediating role of attention deficit in the relationship between insomnia and social cognition. Methods A cross-sectional survey was carried out among 664 nurses (Mage = 33.03 years; SD ± 6.93 years) from December 2020 to September 2021. They completed the Scale of Attitude towards the Patient (SAtP), the Athens Insomnia Scale (AIS), a single-item numeric rating scale assessing the increasing severity of attention complaints, and questions relating to socio-demographic information. The analysis was carried out by examining the mediating role of attention deficit in the relationship between insomnia and social cognition. Results The prevalence of insomnia symptoms was high (52% insomnia using the AIS). Insomnia was significantly correlated with attention problems (b = 0.18, standard e...
Computer Systems Science and Engineering
In this paper, the feasibility of automated and accurate in vivo measurements of vascular paramet... more In this paper, the feasibility of automated and accurate in vivo measurements of vascular parameters continuously and non-invasively using ultrasound sensor is presented. Vascular parameters such as pulse wave velocity (PWV), blood pressure (BP), arterial compliance (AC) and stiffness index (SI) are affluent indicators of cardiovascular disorders and needs to be monitored non-invasively and continuously during surgeries and follow-up procedures. Cuff based or invasive catheter techniques are considered as gold standard to measure BP and are fed manually to compute AC and SI which employ imaging algorithms. In this context, a Continuous and Non-Invasive Vascular Stiffness and Arterial Compliance Screener (CaNVAS) is developed to measure said parameters continuously and non-invasively using ultrasound sensor. Acoustic waves of 5 MHz (2.2 – 10 MHz) are driven through target arterial walls, reflected echoes captured, pre-processed and frequency shift is used to calculate PWV. It is obse...
International Journal of Environmental Research and Public Health
This article is an open access article distributed under the terms and conditions of the Creative... more This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY
Journal of Mechanics in Medicine and Biology
Mitral Stenosis (MS) is an abnormal condition of the heart mitral valve in which the valve orific... more Mitral Stenosis (MS) is an abnormal condition of the heart mitral valve in which the valve orifice area is reduced leading to many complications in heart function. Noninvasive and less expensive procedures for diagnosis are not currently available. The aim of this work was to explore the use of the radial artery pulse (RAP) to diagnose MS. This paper analyzed the effect of the development and growth of MS on possible radial artery noninvasive assessment parameters. For this, MS was introduced to ex vivo by varying the orifice area to either 1, 2, 3, 4 or 5[Formula: see text]cm2 in a hybrid cardiopulmonary electrical analogous model based on clinically obtained healthy controls with an orifice area of 6[Formula: see text]cm2. Results showed that a mitral valve area less than 2[Formula: see text]cm2 significantly influenced the pulse magnitude and time parameters. A strong correlation was observed in pulse height (PH), mean pulse height (MPH), and time occurrence of the dichotic notch...
Annals of Biomedical Engineering, 2010
This article investigates the possibility of extracting gastric motility (GM) information from fi... more This article investigates the possibility of extracting gastric motility (GM) information from finger photoplethysmographic (PPG) signals non-invasively. Now-a-days measuring GM is a challenging task because of invasive and complicated clinical procedures involved. It is well-known that the PPG signal acquired from finger consists of information related to heart rate and respiratory rate. This thread is taken further and effort has been put here to find whether it is possible to extract GM information from finger PPG in an easier way and without discomfort to the patients. Finger PPG and GM (measured using Electrogastrogram, EGG) signals were acquired simultaneously at the rate of 100 Hz from eight healthy subjects for 30 min duration in fasting and postprandial states. In this study, we process the finger PPG signal and extract a slow wave that is analogous to actual EGG signal. To this end, we chose two advanced signal processing approaches: first, we perform discrete wavelet transform (DWT) to separate the different components, since PPG and EGG signals are non-stationary in nature. Second, in the frequency domain, we perform crossspectral and coherence analysis using autoregressive (AR) spectral estimation method in order to compare the spectral details of recorded PPG and EGG signals. In DWT, a lower frequency oscillation (%0.05 Hz) called slow wave was extracted from PPG signal which looks similar to the slow wave of GM in both shape and frequency in the range (0-0.1953) Hz. Comparison of these two slow wave signals was done by normalized cross-correlation technique. Crosscorrelation values are found to be high (range 0.68-0.82, SD 0.12, R = 1.0 indicates exact agreement, p < 0.05) for all subjects and there is no significant difference in crosscorrelation between fasting and postprandial states. The coherence analysis results demonstrate that a moderate coherence (range 0.5-0.7, SD 0.13, p < 0.05) exists between EGG and PPG signal in the ''slow wave'' frequency band, without any significant change in the level of coherence in postprandial state. These results indicate that finger PPG signal contains GM-related information. The findings are sufficiently encouraging to motivate further exploration of finger PPG as a non-invasive source of GM-related information.
Journal of Food Quality, May 6, 2022
Deep learning (DL) is a new approach that provides exceptional speed in healthcare activities wit... more Deep learning (DL) is a new approach that provides exceptional speed in healthcare activities with greater accuracy. In this regard, "convolutional neural network" or CNN and blockchain are two important parts that together fasten the disease detection procedures securely. CNN can detect and predict diseases like lung cancer and help determine food quality, and blockchain is responsible for data. is research is going to analyze the extension of blockchain with the help of CNN for lung cancer prediction and making food safer. CNN algorithm has been trained with a huge number of images by altering the filters, features, epoch values, padding value, kernel size, and resolution. Subsequently, the CNN accuracy has been measured to understand how these factors affect the accuracy. A linear regression analysis has been carried out in IBM SPSS where the independent variables selected are image dataset augmentation, epochs, features, pixel size (90 × 90 to 512 × 512), kernel size (0-7), filters (10-40), and padding. e dependent variable is the accuracy of CNN. Findings suggested that a larger number of epochs improve the CNN accuracy; however, when more than 12 epochs are considered, the accuracy may decrease. A greater pixel/resolution also improves the accuracy of cancer and food image detection. When images are provided with excellent features and filters, the CNN accuracy improves. e main objective of this research is to comprehend how the independent variables affect the accuracy (dependent), but the reading may not be fully exact, and thus, the researcher has conceded out a minor task, which delivered evidence supportive of the analysis and against the analysis. As a result, it can be determined that image augmentation and a large number of images develop the CNN accuracy in lung cancer prediction and food safety determination when features and filters are applied correctly. A total of 10-12 epochs are desirable for CNN to receive 99% accuracy with 1 padding.
Computers, Materials & Continua
The Journal of Supercomputing
The Journal of Supercomputing
Computers, Materials & Continua, 2021
Contrast Media & Molecular Imaging, 2022
Biomedical imaging technologies are designed to offer functional, anatomical, and molecular detai... more Biomedical imaging technologies are designed to offer functional, anatomical, and molecular details related to the internal organs. Photoacoustic imaging (PAI) is becoming familiar among researchers and industrialists. The PAI is found useful in several applications of brain and cancer imaging such as prostate cancer, breast cancer, and ovarian cancer. At the same time, the vessel images hold important medical details which offer strategies for a qualified diagnosis. Recently developed image processing techniques can be employed to segment vessels. Since vessel segmentation on PAI is a difficult process, this paper employs metaheuristic optimization-based vascular segmentation techniques for PAI. The proposed model involves two distinct kinds of vessel segmentation approaches such as Shannon’s entropy function (SEF) and multilevel Otsu thresholding (MLOT). Moreover, the threshold value and entropy function in the segmentation process are optimized using three metaheuristics such as ...
Journal of Intercultural Ethnopharmacology, 2012
We report an unusual incidental radiographic finding of this 71 year old Malay lady who suffered ... more We report an unusual incidental radiographic finding of this 71 year old Malay lady who suffered a closed neck of femur fracture due a fall at home which had undergone total hip replacement at our establishment .This is one of the only papers showing incidental occurrence of susuk or charm needles in hip region in orthopaedic field.
Nature and Science of Sleep
Few studies have investigated the validity of the Athens insomnia scale (AIS) using a robust appr... more Few studies have investigated the validity of the Athens insomnia scale (AIS) using a robust approach of both classical theory and the rating scale model. Therefore, in this study, we investigated psychometric validation of the AIS using both of these approaches in nurses. Methods: Nurses (n= 563, age= 33.2±7.1 years) working in health facilities in Saudi Arabia participated in a cross-sectional study. Participants completed the AIS, socio-demographics tool, and sleep health-related questions. Results: Confirmatory factor analysis (CFA) favored a 2-factor structure with both comparative fit index (CFI), and incremental fit index (IFI) having values above 0.95. The 2-factor model had the lowest values of Akaike information criterion (AIC), root mean square error of approximation (RMSEA), χ 2 , and χ 2 /df. This 2-factor structure showed configural invariance (CFI more than 0.95, RMSEA less than 0.08, and Χ 2 /df less than 3), and metric, scalar, and strict invariance (based on Δ CFI ≤-0.01, and Δ RMSEA ≥ 0.015 criteria). No ceiling/floor effects were seen for the AIS total scores. Infit and outfit mean square values for all the items were within the acceptable range (<1.4, >0.6). The threshold estimates for each item were ordered as expected. Cronbach's α for the AIS tool, factor-1 score, factor-2 score was 0.86, 0.82, and 0.72, respectively. AIS factor scores-1/2 were significantly associated with a habitual feeling of tiredness after usual night sleep (p<0.001), Impairment of daytime socio-occupational functioning (p<0.05), and with a feeling of daytime fatigue, irritability, and restlessness (p<0.05). Conclusion: The findings favor the validity of a 2-factor structure of the AIS with adequate item properties, convergent validity, and reliability in nurses.
This work presents a portable, affordable and reliable vein locating device to overcome the compl... more This work presents a portable, affordable and reliable vein locating device to overcome the complications in vein localization irrespective of age and tissue thickness during medical procedures like Phlebotomy and intravenous infusion. A prototype has been developed using infrared (IR) detector and multispectral near infrared (NIR) (740,765,770,780 nm) source. The differential absorption of the NIR by veins due to the presence of deoxyhemoglobin, helps in enhancing the localization of the vein. The detector is integrated with the single board computer (SBC) and connected with LCD through serial programming interface (SPI) for real time display of veins. The initial observations have found to be successful. It is expected that this affordable device will help in reducing time and improving accessibility to locate antecubital and cephalic vein without multiple incision and minimal pain.
Earth Science Informatics
Computers, Materials & Continua
Interdisciplinary Sciences: Computational Life Sciences, 2021
Diabetic retinopathy (DR) is one of the most prevalent genetic diseases in human and it is caused... more Diabetic retinopathy (DR) is one of the most prevalent genetic diseases in human and it is caused by damage to the blood vessels in the eye retina. If it is undetected and untreated at right time, it can lead to vision loss. There are many medical imaging and processing technologies to improve the diagnostic process of DR to overcome the lack of human experts. In the existing image processing methods, there are issues such as lack of noise removal, improper clustering segmentation and less classification accuracy. This can be accomplished by automatic diagnosis of DR using advanced image processing method. The cotton wool spot (CWS), hard exudates (HE) contains a common manifestation of many diseases in retina including DR and acquired immunodeficiency syndrome. In the present work, super iterative clustering algorithm (SICA) is proposed to identify the CWS, HE on retinal image. Feature-based medical image retrieval (FBMIR) datasets are utilized for this purpose. Noises present on t...
Turkish Journal of Physiotherapy and Rehabilitation, 2021
According to consensus, the use of Computerized Tomography (CT) methodology for early finding of ... more According to consensus, the use of Computerized Tomography (CT) methodology for early finding of several disease, yields both quick and reliable results. Expert radiologists reported that COVID19 has exhibit severalmanners in CT images. In this research, a novel technique of fusing and rankingfeatures based Deep Learning Approach was proposed to detect COVID-19 in its early stages. To create sub-datasets, 32x32 as Subset-1 and 64x64 as Subset-2, within the framework of the proposed procedure, 300 patch images as COVID-19 and Non-COVID-19 were used in the training and testing phases. A VB-Net Deep learning-based segmentation system was created to segment the infection regions in CT scans image of COVID-19 patients. To improve the proposed methodperformance, feature fusion and a ranking method were used.The Convolutional Neural Network (CNN) technique is used in transfer learning. The processed data was then categorized into two types as by using a Support Vector Machine (SVM). This s...
PeerJ
Purpose Insomnia-related affective functional disorder may negatively affect social cognition suc... more Purpose Insomnia-related affective functional disorder may negatively affect social cognition such as empathy, altruism, and attitude toward providing care. No previous studies have ever investigated the mediating role of attention deficit in the relationship between insomnia and social cognition. Methods A cross-sectional survey was carried out among 664 nurses (Mage = 33.03 years; SD ± 6.93 years) from December 2020 to September 2021. They completed the Scale of Attitude towards the Patient (SAtP), the Athens Insomnia Scale (AIS), a single-item numeric rating scale assessing the increasing severity of attention complaints, and questions relating to socio-demographic information. The analysis was carried out by examining the mediating role of attention deficit in the relationship between insomnia and social cognition. Results The prevalence of insomnia symptoms was high (52% insomnia using the AIS). Insomnia was significantly correlated with attention problems (b = 0.18, standard e...
Computer Systems Science and Engineering
In this paper, the feasibility of automated and accurate in vivo measurements of vascular paramet... more In this paper, the feasibility of automated and accurate in vivo measurements of vascular parameters continuously and non-invasively using ultrasound sensor is presented. Vascular parameters such as pulse wave velocity (PWV), blood pressure (BP), arterial compliance (AC) and stiffness index (SI) are affluent indicators of cardiovascular disorders and needs to be monitored non-invasively and continuously during surgeries and follow-up procedures. Cuff based or invasive catheter techniques are considered as gold standard to measure BP and are fed manually to compute AC and SI which employ imaging algorithms. In this context, a Continuous and Non-Invasive Vascular Stiffness and Arterial Compliance Screener (CaNVAS) is developed to measure said parameters continuously and non-invasively using ultrasound sensor. Acoustic waves of 5 MHz (2.2 – 10 MHz) are driven through target arterial walls, reflected echoes captured, pre-processed and frequency shift is used to calculate PWV. It is obse...
International Journal of Environmental Research and Public Health
This article is an open access article distributed under the terms and conditions of the Creative... more This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY
Journal of Mechanics in Medicine and Biology
Mitral Stenosis (MS) is an abnormal condition of the heart mitral valve in which the valve orific... more Mitral Stenosis (MS) is an abnormal condition of the heart mitral valve in which the valve orifice area is reduced leading to many complications in heart function. Noninvasive and less expensive procedures for diagnosis are not currently available. The aim of this work was to explore the use of the radial artery pulse (RAP) to diagnose MS. This paper analyzed the effect of the development and growth of MS on possible radial artery noninvasive assessment parameters. For this, MS was introduced to ex vivo by varying the orifice area to either 1, 2, 3, 4 or 5[Formula: see text]cm2 in a hybrid cardiopulmonary electrical analogous model based on clinically obtained healthy controls with an orifice area of 6[Formula: see text]cm2. Results showed that a mitral valve area less than 2[Formula: see text]cm2 significantly influenced the pulse magnitude and time parameters. A strong correlation was observed in pulse height (PH), mean pulse height (MPH), and time occurrence of the dichotic notch...
Annals of Biomedical Engineering, 2010
This article investigates the possibility of extracting gastric motility (GM) information from fi... more This article investigates the possibility of extracting gastric motility (GM) information from finger photoplethysmographic (PPG) signals non-invasively. Now-a-days measuring GM is a challenging task because of invasive and complicated clinical procedures involved. It is well-known that the PPG signal acquired from finger consists of information related to heart rate and respiratory rate. This thread is taken further and effort has been put here to find whether it is possible to extract GM information from finger PPG in an easier way and without discomfort to the patients. Finger PPG and GM (measured using Electrogastrogram, EGG) signals were acquired simultaneously at the rate of 100 Hz from eight healthy subjects for 30 min duration in fasting and postprandial states. In this study, we process the finger PPG signal and extract a slow wave that is analogous to actual EGG signal. To this end, we chose two advanced signal processing approaches: first, we perform discrete wavelet transform (DWT) to separate the different components, since PPG and EGG signals are non-stationary in nature. Second, in the frequency domain, we perform crossspectral and coherence analysis using autoregressive (AR) spectral estimation method in order to compare the spectral details of recorded PPG and EGG signals. In DWT, a lower frequency oscillation (%0.05 Hz) called slow wave was extracted from PPG signal which looks similar to the slow wave of GM in both shape and frequency in the range (0-0.1953) Hz. Comparison of these two slow wave signals was done by normalized cross-correlation technique. Crosscorrelation values are found to be high (range 0.68-0.82, SD 0.12, R = 1.0 indicates exact agreement, p < 0.05) for all subjects and there is no significant difference in crosscorrelation between fasting and postprandial states. The coherence analysis results demonstrate that a moderate coherence (range 0.5-0.7, SD 0.13, p < 0.05) exists between EGG and PPG signal in the ''slow wave'' frequency band, without any significant change in the level of coherence in postprandial state. These results indicate that finger PPG signal contains GM-related information. The findings are sufficiently encouraging to motivate further exploration of finger PPG as a non-invasive source of GM-related information.
Journal of Food Quality, May 6, 2022
Deep learning (DL) is a new approach that provides exceptional speed in healthcare activities wit... more Deep learning (DL) is a new approach that provides exceptional speed in healthcare activities with greater accuracy. In this regard, "convolutional neural network" or CNN and blockchain are two important parts that together fasten the disease detection procedures securely. CNN can detect and predict diseases like lung cancer and help determine food quality, and blockchain is responsible for data. is research is going to analyze the extension of blockchain with the help of CNN for lung cancer prediction and making food safer. CNN algorithm has been trained with a huge number of images by altering the filters, features, epoch values, padding value, kernel size, and resolution. Subsequently, the CNN accuracy has been measured to understand how these factors affect the accuracy. A linear regression analysis has been carried out in IBM SPSS where the independent variables selected are image dataset augmentation, epochs, features, pixel size (90 × 90 to 512 × 512), kernel size (0-7), filters (10-40), and padding. e dependent variable is the accuracy of CNN. Findings suggested that a larger number of epochs improve the CNN accuracy; however, when more than 12 epochs are considered, the accuracy may decrease. A greater pixel/resolution also improves the accuracy of cancer and food image detection. When images are provided with excellent features and filters, the CNN accuracy improves. e main objective of this research is to comprehend how the independent variables affect the accuracy (dependent), but the reading may not be fully exact, and thus, the researcher has conceded out a minor task, which delivered evidence supportive of the analysis and against the analysis. As a result, it can be determined that image augmentation and a large number of images develop the CNN accuracy in lung cancer prediction and food safety determination when features and filters are applied correctly. A total of 10-12 epochs are desirable for CNN to receive 99% accuracy with 1 padding.
Computers, Materials & Continua
The Journal of Supercomputing
The Journal of Supercomputing
Computers, Materials & Continua, 2021
Contrast Media & Molecular Imaging, 2022
Biomedical imaging technologies are designed to offer functional, anatomical, and molecular detai... more Biomedical imaging technologies are designed to offer functional, anatomical, and molecular details related to the internal organs. Photoacoustic imaging (PAI) is becoming familiar among researchers and industrialists. The PAI is found useful in several applications of brain and cancer imaging such as prostate cancer, breast cancer, and ovarian cancer. At the same time, the vessel images hold important medical details which offer strategies for a qualified diagnosis. Recently developed image processing techniques can be employed to segment vessels. Since vessel segmentation on PAI is a difficult process, this paper employs metaheuristic optimization-based vascular segmentation techniques for PAI. The proposed model involves two distinct kinds of vessel segmentation approaches such as Shannon’s entropy function (SEF) and multilevel Otsu thresholding (MLOT). Moreover, the threshold value and entropy function in the segmentation process are optimized using three metaheuristics such as ...
Journal of Intercultural Ethnopharmacology, 2012
We report an unusual incidental radiographic finding of this 71 year old Malay lady who suffered ... more We report an unusual incidental radiographic finding of this 71 year old Malay lady who suffered a closed neck of femur fracture due a fall at home which had undergone total hip replacement at our establishment .This is one of the only papers showing incidental occurrence of susuk or charm needles in hip region in orthopaedic field.
Nature and Science of Sleep
Few studies have investigated the validity of the Athens insomnia scale (AIS) using a robust appr... more Few studies have investigated the validity of the Athens insomnia scale (AIS) using a robust approach of both classical theory and the rating scale model. Therefore, in this study, we investigated psychometric validation of the AIS using both of these approaches in nurses. Methods: Nurses (n= 563, age= 33.2±7.1 years) working in health facilities in Saudi Arabia participated in a cross-sectional study. Participants completed the AIS, socio-demographics tool, and sleep health-related questions. Results: Confirmatory factor analysis (CFA) favored a 2-factor structure with both comparative fit index (CFI), and incremental fit index (IFI) having values above 0.95. The 2-factor model had the lowest values of Akaike information criterion (AIC), root mean square error of approximation (RMSEA), χ 2 , and χ 2 /df. This 2-factor structure showed configural invariance (CFI more than 0.95, RMSEA less than 0.08, and Χ 2 /df less than 3), and metric, scalar, and strict invariance (based on Δ CFI ≤-0.01, and Δ RMSEA ≥ 0.015 criteria). No ceiling/floor effects were seen for the AIS total scores. Infit and outfit mean square values for all the items were within the acceptable range (<1.4, >0.6). The threshold estimates for each item were ordered as expected. Cronbach's α for the AIS tool, factor-1 score, factor-2 score was 0.86, 0.82, and 0.72, respectively. AIS factor scores-1/2 were significantly associated with a habitual feeling of tiredness after usual night sleep (p<0.001), Impairment of daytime socio-occupational functioning (p<0.05), and with a feeling of daytime fatigue, irritability, and restlessness (p<0.05). Conclusion: The findings favor the validity of a 2-factor structure of the AIS with adequate item properties, convergent validity, and reliability in nurses.
This work presents a portable, affordable and reliable vein locating device to overcome the compl... more This work presents a portable, affordable and reliable vein locating device to overcome the complications in vein localization irrespective of age and tissue thickness during medical procedures like Phlebotomy and intravenous infusion. A prototype has been developed using infrared (IR) detector and multispectral near infrared (NIR) (740,765,770,780 nm) source. The differential absorption of the NIR by veins due to the presence of deoxyhemoglobin, helps in enhancing the localization of the vein. The detector is integrated with the single board computer (SBC) and connected with LCD through serial programming interface (SPI) for real time display of veins. The initial observations have found to be successful. It is expected that this affordable device will help in reducing time and improving accessibility to locate antecubital and cephalic vein without multiple incision and minimal pain.
Earth Science Informatics
Computers, Materials & Continua
Interdisciplinary Sciences: Computational Life Sciences, 2021
Diabetic retinopathy (DR) is one of the most prevalent genetic diseases in human and it is caused... more Diabetic retinopathy (DR) is one of the most prevalent genetic diseases in human and it is caused by damage to the blood vessels in the eye retina. If it is undetected and untreated at right time, it can lead to vision loss. There are many medical imaging and processing technologies to improve the diagnostic process of DR to overcome the lack of human experts. In the existing image processing methods, there are issues such as lack of noise removal, improper clustering segmentation and less classification accuracy. This can be accomplished by automatic diagnosis of DR using advanced image processing method. The cotton wool spot (CWS), hard exudates (HE) contains a common manifestation of many diseases in retina including DR and acquired immunodeficiency syndrome. In the present work, super iterative clustering algorithm (SICA) is proposed to identify the CWS, HE on retinal image. Feature-based medical image retrieval (FBMIR) datasets are utilized for this purpose. Noises present on t...
Turkish Journal of Physiotherapy and Rehabilitation, 2021
According to consensus, the use of Computerized Tomography (CT) methodology for early finding of ... more According to consensus, the use of Computerized Tomography (CT) methodology for early finding of several disease, yields both quick and reliable results. Expert radiologists reported that COVID19 has exhibit severalmanners in CT images. In this research, a novel technique of fusing and rankingfeatures based Deep Learning Approach was proposed to detect COVID-19 in its early stages. To create sub-datasets, 32x32 as Subset-1 and 64x64 as Subset-2, within the framework of the proposed procedure, 300 patch images as COVID-19 and Non-COVID-19 were used in the training and testing phases. A VB-Net Deep learning-based segmentation system was created to segment the infection regions in CT scans image of COVID-19 patients. To improve the proposed methodperformance, feature fusion and a ranking method were used.The Convolutional Neural Network (CNN) technique is used in transfer learning. The processed data was then categorized into two types as by using a Support Vector Machine (SVM). This s...