The histrionic growth of mobile subscribers, disruptive ecosystems such as IoT-based applications... more The histrionic growth of mobile subscribers, disruptive ecosystems such as IoT-based applications, and astounding channel capacity requirements to connect trillions of devices are massive challenges of the earlier mobile generations, 5G turned up the key solution. The prime objective of the 5G network is not only to maintain a 1000-fold capacity gain and 10 Giga Bits per second delivered to a single user, but it also assured quality-of-service, higher spectral efficiency, the ultra-reliable and improved battery lifetime of devices and massive machine-type communication (mMTC). The huge traffic load and high amount of resource consumption in 5G applications, augmented reality and virtual reality for magnificent virtual experience, and wireless body area networks will seriously affect the channel capacity of cellular cells and interrupt the admission and service of other users which makes compulsory new means of channel capacity and spectral efficiency enhancement techniques. In this ...
2020 IEEE 23rd International Multitopic Conference (INMIC)
Pneumonia known as a “silent killer” is a worldwide health issue, causing a large number of morta... more Pneumonia known as a “silent killer” is a worldwide health issue, causing a large number of mortality. In developing countries, the indication of this lung's disease makes it one of the deadliest among children under the age of five years old. The numerical contrast between infection rates and death rates shows how much the early diagnosis of pneumonia is crucial. To overcome this crucial issue, accurately and fast diagnose is required for timely treatment. The Chest X-rays (CXR) is the best choice in the term of cost and availability to diagnose pneumonia. This paper presents a supervised computer aided diagnostic (CAD) system for the classification of the infected lung with pneumonia and the normal X-ray image. The CAD system can process hundreds of X-rays images to extract features using the Histogram of Oriented Gradient (HOG) technique. Then, we trained three different classifier: Support Vector Machine (SVM), decision Tree and Random Forest to classify the extracted features. The largest publicly available chest X-ray dataset contains 5,232 frontal view images is used for testing and validation. Performance parameters accuracy, recall, precision and F1-score are compared with the existing literature to check the effectiveness of the proposed model.
Communications in Computer and Information Science, 2020
In the last two decades, significant advancement occurs related to medical imaging modalities and... more In the last two decades, significant advancement occurs related to medical imaging modalities and image processing techniques. In biomedical imaging, the accuracy of a diagnosed area of interest can be increased using a multimodal dataset of patients. A lot of research and techniques are proposed for processing and analysis of multimodal imaging, which requires datasets for benchmarking and validation of their performances. In this connection, two important databases: MIDAS and OASIS are selected and evaluated for the guidance of the researcher to perform their results in the field of multimodal imaging. The associated diseases to these datasets and open issues in the field of multimodal imaging are also discussed. The main objective of this article is to discuss the current interest of the researcher and open platforms for future research in multimodal medical imaging. We originate some statistical results of graphs and charts using the online Web Analysis tool “SIMILIARWEB” to show public interest on these databases and also arranged these datasets according to various modalities, body scanned areas, disease-based and classification of images to motivate researchers working in multimodal medical areas. The significance of these databases in the field of multimodal image processing is encapsulated by graphical charts and statistical results.
Communications in Computer and Information Science, 2020
Automated brain tumor detection is an important application in the medical field. There is a lot ... more Automated brain tumor detection is an important application in the medical field. There is a lot of methods developed for this task. In this paper, we have implemented an algorithm which detects the type of brain tumor from MRI image using supervised classification techniques. The major part of the work includes feature extraction using DWT and then reduction of features by using PCA. These reduced features are submitted to different classifiers like SVM, k-NN, Naive Bayes and LDA. The results from each classifier are then submitted to a voting algorithm that chooses the most frequent result. The dataset for training contains 160 MRI images. The algorithm is processed on 200 * 200 images to reduce processing time. This method is tested and found to be much beneficial and rapid. It could be utilized in the field of MRI classification and can assist doctors to detect the tumor type and diagnose about patient abnormality level.
In his 1987 entry on 'Perfect Competition' in The New Palgrave, the author reviewed the question ... more In his 1987 entry on 'Perfect Competition' in The New Palgrave, the author reviewed the question of the perfectness of perfect competition, and gave four alternative formalisations rooted in the so-called Arrow-Debreu-Mckenzie model. That entry is now updated for the second edition to include work done on the subject during the last twenty years. A fresh assessment of this literature is offered, one that emphasises the independence assumption whereby individual agents are not related except through the price system. And it highlights a 'linguistic turn' whereby Hayek's two fundamental papers on 'division of knowledge' are seen to have devastating consequences for this research programme.
The objective of the present piece of work was to the development and psychometric assessment of ... more The objective of the present piece of work was to the development and psychometric assessment of social support scale for within country migrated students (SSS-WCMS). Following the incidental cum random sampling technique, 200 North Indian students within the age range of 18 to 24 years were drawn from different colleges of Warangal districts, Telangana, India. Dimensions of social support were decided on the basis of literature. Items were pooled out by unstructured interviews. Exploratory factor analysis (FEA) of 18-item pool yielded a 14-item measure with four independent dimensions viz. emotional support, informational support, companionship support and tangible support. The items communalities ranges are greater than .400. Overall variance explained by all these factors is 53.90%. Confirmatory factor analysis also confirmed the explored all four factors from the EFA. The findings indicated that SSS-WCMS has sufficient convergent and discriminant validity. The composite reliabil...
2020 IEEE 23rd International Multitopic Conference (INMIC), 2020
The rapid development of digital imaging and computer vision has extended the potential of using ... more The rapid development of digital imaging and computer vision has extended the potential of using these technologies in the diagnosis of human diseases. Medical image analysis is a non-invasive way to identify human diseases which are usually manually marked by medical experts or automatically detected by the Computer-Aided Diagnostic (CAD) system. The fundus images provide facts and information about visual disorders (diabetic retinopathy, glaucoma, age-related macular degeneration, etc.), brain disease (Alzheimer's), and heart-related diseases (cardiovascular, hypertension, and stroke). Extensive research has been done in the last two decades in developing automated methods for the identification of various human disorders from fundus images. This survey paper provides the reader with a broad review of the fundus image processing for the identification of various human disorders. In this paper, human diseases that can be diagnosed through fundus images are reviewed. Several publicly available fundus datasets which are helpful in the screening of these abnormalities are briefly discussed. This work aims to show the importance of retinal images in the diagnosis of different human diseases. The main challenges and difficulties faced in effective diagnosis are presented and discussed. We believe that this work will guide the researchers in addressing the challenges in existing solutions and assist doctors in the proper diagnosis of various diseases.
Optic Disc (OD) recognition is a fundamental phase in the developing methods for automated analys... more Optic Disc (OD) recognition is a fundamental phase in the developing methods for automated analysis of different chronic ocular disorders. In this article, a novel 46 Khan Bahadar Khan et al. technique has been introduced for OD detection and borderline extraction, which can be witnessed as a milestone in the advancement of a Computer-Assisted Diagnostic (CAD) framework for glaucoma detection in fundus photographs. A unique solution has been presented for removal of illuminated light spots due to refraction of camera light (so called fringe noise) on the edges of the retinal color images, which leads to false detection of OD. An intelligent non-uniform mixing of red and green channels is introduced for denoising of retinal photographs because of the dissimilar noise level in each channel. Template based matching technique is applied for OD localization of retinal image. The approach is thoroughly verified on openly accessible the DRIVE and the STARE datasets for OD detection and denoising of retinal images. This denoising technique greatly improved the accuracy of OD detection in contrast to other contending approaches.
In laparoscopic surgery, image quality is often degraded by surgical smoke or by side effects of ... more In laparoscopic surgery, image quality is often degraded by surgical smoke or by side effects of the illumination system, such as reflections, specularities, and non-uniform illumination. The degraded images complicate the work of the surgeons and may lead to errors in image-guided surgery. Existing enhancement algorithms mainly focus on enhancing global image contrast, overlooking local contrast. Here, we propose a new Patch Adaptive Structure Decomposition utilizing the Multi-Exposure Fusion (PASD-MEF) technique to enhance the local contrast of laparoscopic images for better visualization. The set of under-exposure level images are obtained from a single input blurred image by using gamma correction. Spatial linear saturation is applied to enhance image contrast and to adjust the image saturation. The Multi-Exposure Fusion (MEF) is used on a series of multi-exposure images to obtain a single clear and smoke-free fused image. MEF is applied by using adaptive structure decomposition...
Retinal vessel segmentation (RVS) is a significant source of useful information for monitoring, i... more Retinal vessel segmentation (RVS) is a significant source of useful information for monitoring, identification, initial medication, and surgical development of ophthalmic disorders. Most common disorders, i.e., stroke, diabetic retinopathy (DR), and cardiac diseases, often change the normal structure of the retinal vascular network. A lot of research has been committed to building an automatic RVS system. But, it is still an open issue. In this article, a framework is recommended for RVS with fast execution and competing outcomes. An initial binary image is obtained by the application of the MISODATA on the preprocessed image. For vessel structure enhancement, B-COSFIRE filters are utilized along with thresholding to obtain another binary image. These two binary images are combined by logical AND-type operation. Then, it is fused with the enhanced image of B-COSFIRE filters followed by thresholding to obtain the vessel location map (VLM). The methodology is verified on four differen...
Environmental Science and Pollution Research, 2021
The pro-poor growth and environmental sustainability are the twin agendas widely discussed in env... more The pro-poor growth and environmental sustainability are the twin agendas widely discussed in environmental science literature. The technology-embodied growth helps to attain both agendas through knowledge sharing and technology transfer, which trickle down to the poor income group and improve their living standards. Hence, the role of information and communication technologies (ICTs) is deemed crucial in boosting economic growth and is under deep consideration to establish its role in reducing poverty and environmental pollution. The current study examines the long-run relationship between ICTs, poverty reduction, and ecological degradation in Pakistan using time series data from 1975–2018. The short- and long-run parameter estimates were obtained through the Autoregressive Distributed Lag (ARDL) model for robust inferences. The results substantiate the inverted U-shaped Environmental Kuznets Curve relationship between income and emissions with a turning point at US$1000 in the short-run and US$800 in the long-run. The results confirmed the decisive intervention of ICTs factors in the poverty reduction, i.e., computer communications and mobile-telephone-broadband subscriptions support to reduce poverty incidence with the mediation of inbound FDI in a country. As far as income inequality is concerned, it shows that computer services support minimizing income inequality via a channel of high–technology exports in a country. The technology embodied emissions verified in the long-run, where mobile-telephone-broadband subscriptions increase carbon emissions. Finally, mobile-telephone-broadband subscriptions and inbound FDI both are significant contributors to amplify the country’s economic growth. The results conclude that poverty reduction and environmental sustainability agenda are achieved by developing green ICT infrastructure in a country.
The role of natural resources in promoting economic and financial activities is important for att... more The role of natural resources in promoting economic and financial activities is important for attaining country's economic growth. The study used different natural resource rents, domestic investment, trade openness, per capita income and their resulting impact on financial development in order to assess 'financial resource curse' hypothesis in Pakistan by using a consistent time series data from 1975 to 2017. The study employed ARDL-Bounds testing approach that is fairly worked under different order of integrated variables and displayed short-and long-run parameter estimates. Further, the study used VAR decomposition analysis to generate Impulse Response Function (IRF) and Variance Decomposition Analysis (VDA) to assessed forecasted variance and error shocks over a next 10 year time period. The results show that, in the short-run, initial level of forest rents and oil rents supported the 'natural resource abundance' hypothesis, as both the rents substantially increases country's financial development, however, in the long-run, there is a negative relationship of coal rents, forest rents, natural gas rents, and oil rents with domestic credit to private sector (DCPS), which confirmed the 'natural curse hypothesis' in a country. The domestic investment in the form of gross fixed capital formation (GFCF) largely supported the financial activities with all given resource rents in the models, while country's per capita income unable to signify its positive impact on DCPS under the resource curse environment during the study time period. The other results show that coal rents and oil rents decreases broad money supply whereas natural gas rents decreases market capitalization to validate 'financial resource curse' hypothesis in a country. The results of IRF and VDA approach confirmed the viability of both the competing natural resource theories (i.e., financial resource curse and financial resource blessing hypothesis) under financial development in the next 10 year time period.
Oat is an economically important crop and ranks sixth in world cereal production after maize, whe... more Oat is an economically important crop and ranks sixth in world cereal production after maize, wheat, rice, barley and sorghum. It has been primarily utilized as livestock feed. However, the utilization of oats for human consumption has increased progressively, owing to its dietary and health benefits which relies mainly on the total dietary fibre and β-glucan content, which significantly reduces postprandial blood glucose, insulin and blood lipids, especially serum total and low density lipoprotein cholesterol. Henceforth, enhancing Oat b-glucan content forhuman consumption is desirable. As it is a polygenic trait controlled mainly by genes with additive effects, phenotypic selection for greater b-glucan content would be effective for developing cultivars with elevated b-glucan contents. Oat b-glucan concentration has been found to be positively correlated with protein content and negatively correlated with oil content. β-glucan yield (i.e., Product of grain yield and β-glucan conte...
The visual exploration of retinal blood vessels assists ophthalmologists in the diagnoses of diff... more The visual exploration of retinal blood vessels assists ophthalmologists in the diagnoses of different abnormalities of the eyes such as diabetic retinopathy, glaucoma, cardiovascular ailment, high blood pressure, arteriosclerosis, and age-related macular degeneration. The manual inspection of retinal vasculature is an extremely challenging and tedious task for medical experts due to the complex structure of an eye, tiny blood vessels, and variation in vessels width. Several automatic retinal vessels extraction techniques have been proposed in contemporary literature, which assist ophthalmologists in the timely identification of an eye disorders. However, due to the fast evolution of such techniques, a comprehensive survey is needed. This survey presents a comprehensive review of such techniques, strategies, and algorithms presented to date. The techniques are classified into logical groups based on the underlying methodology employed for retinal vessel extraction. The performance of existing techniques is reported on the publicly accessible datasets in term of various performance measures, providing a valuable comparison among the techniques. Thus, this survey presents a valuable resource for researchers working toward automatic extraction of retinal vessels.
The crowd phenomenon frequently occurs in dense urban living environments. Crowd counting or esti... more The crowd phenomenon frequently occurs in dense urban living environments. Crowd counting or estimation helps to develop management strategies such as designing safe public places and evacuation plan for emergencies. These strategies are different depending upon the type of event such as political and public demonstrations, sports, and religious events. However, estimating the number of people in crowds at closed or open environments is quite challenging because of the dynamics involved in the process. In addition, crowd estimation itself poses challenges due to randomness in crowd behavior, motion, and an area’s geometric specifications. Crowd behavior as well as the area parameters is studied before suggesting any possible technological solution for managing a crowd. This article presents a theoretical understanding of the major crowd size estimation approaches that cannot be achieved through the study of existing survey papers in this area, because the existing survey papers focu...
It is now widely recognized that knowledge assets and technological enhancements are essential st... more It is now widely recognized that knowledge assets and technological enhancements are essential strategic resources for any organisation to achieve competitive advantage and sustainability. The imperative for achieving this efficiency is in transfer of relevant information for decision-making across all levels of company structure. It can be done with well-disposed knowledge management system, that improves the overall corporate performance. This paper examines how companies in Czech Republic manage their internal knowledge associated with environmental sustainability so as to improve their overall corporate performance.
Diabetic Retinopathy (DR) harm retinal blood vessels in the eye causing visual deficiency. The ap... more Diabetic Retinopathy (DR) harm retinal blood vessels in the eye causing visual deficiency. The appearance and structure of blood vessels in retinal images play an essential part in the diagnoses of an eye sicknesses. We proposed a less computational unsupervised automated technique with promising results for detection of retinal vasculature by using morphological hessian based approach and region based Otsu thresholding. Contrast Limited Adaptive Histogram Equalization (CLAHE) and morphological filters have been used for enhancement and to remove low frequency noise or geometrical objects, respectively. The hessian matrix and eigenvalues approach used has been in a modified form at two different scales to extract wide and thin vessel enhanced images separately. Otsu thresholding has been further applied in a novel way to classify vessel and non-vessel pixels from both enhanced images. Finally, postprocessing steps has been used to eliminate the unwanted region/segment, non-vessel pi...
Several empirical piece of research work illustrated that predicting effect of social support on ... more Several empirical piece of research work illustrated that predicting effect of social support on psychological wellbeing. But predicting effect of social support on psychological wellbeing is lacking in Indian perspectives. The purpose of current research work is to examine the predicting effect of social support on psychological wellbeing. Employed stratified disproportional random sampling technique 200 elderly within the age range of 60 to 70 years were selected from Chhattisgarh State. Correlational research design was employed in present research work. Psychological wellbeing was assessed by PGI general wellbeing questionnaire (Verma & Verma, 1989). Social support was assessed by self developed social support questionnaire. Predicting effect was examining by hierarchal regression analysis. Control factors (socio-demographic factors) explained 18% of total variance (R2=.180; F (5, 194) = 100.250; p<0.01). Social support explained an additional 20% (F (1,193) = 35.121, p<0....
Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer, Jan 6, 2015
The present study was designed to validate the Hindi version of the Multidimensional Fatigue Inve... more The present study was designed to validate the Hindi version of the Multidimensional Fatigue Inventory-20 (MFI-20) in Indian oncology population. The original English version of the MFI-20 was translated into Hindi (hMFI-20) using the translation and back translation processes. The hMFI-20 was administered to 200 cancer patients. The item analysis for hMFI-20 was carried out using the corrected item-total correlation. The confirmatory factor analysis (CFA) was employed to test whether the original factor structure of MFI-20 is confirmed for the hMFI-20. Further, convergent and discriminant validities were also tested. The reliability of the hMFI-20 was evaluated by computing composite reliability and Cronbach's α coefficient. Corrected item-total correlation value for each of the items of hMFI-20 was greater than 0.6. Results of the CFA (comparative fit indices (CFI) = 0.91, root mean squared residual (RMR) = 0.04, root mean square error of approximation (RMSEA) = 0.028, and χ (...
This study is a piece of empirical research work which aims to examine the prediction effect of o... more This study is a piece of empirical research work which aims to examine the prediction effect of organizational attractiveness on employee retention. Following the incidental cum random sampling technique 200 State bank of India (III class) employee were drawn from Chhattisgarh state to serve as participants in the present research work. In the present research work correlational research design was employed. Organizational attractiveness was measured by organizational attractiveness scale (Highhouse et. al., 2003). Employee retention was measured by employee retention questionnaire . Prediction effect was examining using by hierarchical regression analysis. The result of the present study indicates that in organizational attractiveness emerged as a significant predictor of employee retention. There is sufficient empirical and statistical evidence of the prediction effect of organizational attractiveness on employee retention in state bank of India III class employee.
The histrionic growth of mobile subscribers, disruptive ecosystems such as IoT-based applications... more The histrionic growth of mobile subscribers, disruptive ecosystems such as IoT-based applications, and astounding channel capacity requirements to connect trillions of devices are massive challenges of the earlier mobile generations, 5G turned up the key solution. The prime objective of the 5G network is not only to maintain a 1000-fold capacity gain and 10 Giga Bits per second delivered to a single user, but it also assured quality-of-service, higher spectral efficiency, the ultra-reliable and improved battery lifetime of devices and massive machine-type communication (mMTC). The huge traffic load and high amount of resource consumption in 5G applications, augmented reality and virtual reality for magnificent virtual experience, and wireless body area networks will seriously affect the channel capacity of cellular cells and interrupt the admission and service of other users which makes compulsory new means of channel capacity and spectral efficiency enhancement techniques. In this ...
2020 IEEE 23rd International Multitopic Conference (INMIC)
Pneumonia known as a “silent killer” is a worldwide health issue, causing a large number of morta... more Pneumonia known as a “silent killer” is a worldwide health issue, causing a large number of mortality. In developing countries, the indication of this lung's disease makes it one of the deadliest among children under the age of five years old. The numerical contrast between infection rates and death rates shows how much the early diagnosis of pneumonia is crucial. To overcome this crucial issue, accurately and fast diagnose is required for timely treatment. The Chest X-rays (CXR) is the best choice in the term of cost and availability to diagnose pneumonia. This paper presents a supervised computer aided diagnostic (CAD) system for the classification of the infected lung with pneumonia and the normal X-ray image. The CAD system can process hundreds of X-rays images to extract features using the Histogram of Oriented Gradient (HOG) technique. Then, we trained three different classifier: Support Vector Machine (SVM), decision Tree and Random Forest to classify the extracted features. The largest publicly available chest X-ray dataset contains 5,232 frontal view images is used for testing and validation. Performance parameters accuracy, recall, precision and F1-score are compared with the existing literature to check the effectiveness of the proposed model.
Communications in Computer and Information Science, 2020
In the last two decades, significant advancement occurs related to medical imaging modalities and... more In the last two decades, significant advancement occurs related to medical imaging modalities and image processing techniques. In biomedical imaging, the accuracy of a diagnosed area of interest can be increased using a multimodal dataset of patients. A lot of research and techniques are proposed for processing and analysis of multimodal imaging, which requires datasets for benchmarking and validation of their performances. In this connection, two important databases: MIDAS and OASIS are selected and evaluated for the guidance of the researcher to perform their results in the field of multimodal imaging. The associated diseases to these datasets and open issues in the field of multimodal imaging are also discussed. The main objective of this article is to discuss the current interest of the researcher and open platforms for future research in multimodal medical imaging. We originate some statistical results of graphs and charts using the online Web Analysis tool “SIMILIARWEB” to show public interest on these databases and also arranged these datasets according to various modalities, body scanned areas, disease-based and classification of images to motivate researchers working in multimodal medical areas. The significance of these databases in the field of multimodal image processing is encapsulated by graphical charts and statistical results.
Communications in Computer and Information Science, 2020
Automated brain tumor detection is an important application in the medical field. There is a lot ... more Automated brain tumor detection is an important application in the medical field. There is a lot of methods developed for this task. In this paper, we have implemented an algorithm which detects the type of brain tumor from MRI image using supervised classification techniques. The major part of the work includes feature extraction using DWT and then reduction of features by using PCA. These reduced features are submitted to different classifiers like SVM, k-NN, Naive Bayes and LDA. The results from each classifier are then submitted to a voting algorithm that chooses the most frequent result. The dataset for training contains 160 MRI images. The algorithm is processed on 200 * 200 images to reduce processing time. This method is tested and found to be much beneficial and rapid. It could be utilized in the field of MRI classification and can assist doctors to detect the tumor type and diagnose about patient abnormality level.
In his 1987 entry on 'Perfect Competition' in The New Palgrave, the author reviewed the question ... more In his 1987 entry on 'Perfect Competition' in The New Palgrave, the author reviewed the question of the perfectness of perfect competition, and gave four alternative formalisations rooted in the so-called Arrow-Debreu-Mckenzie model. That entry is now updated for the second edition to include work done on the subject during the last twenty years. A fresh assessment of this literature is offered, one that emphasises the independence assumption whereby individual agents are not related except through the price system. And it highlights a 'linguistic turn' whereby Hayek's two fundamental papers on 'division of knowledge' are seen to have devastating consequences for this research programme.
The objective of the present piece of work was to the development and psychometric assessment of ... more The objective of the present piece of work was to the development and psychometric assessment of social support scale for within country migrated students (SSS-WCMS). Following the incidental cum random sampling technique, 200 North Indian students within the age range of 18 to 24 years were drawn from different colleges of Warangal districts, Telangana, India. Dimensions of social support were decided on the basis of literature. Items were pooled out by unstructured interviews. Exploratory factor analysis (FEA) of 18-item pool yielded a 14-item measure with four independent dimensions viz. emotional support, informational support, companionship support and tangible support. The items communalities ranges are greater than .400. Overall variance explained by all these factors is 53.90%. Confirmatory factor analysis also confirmed the explored all four factors from the EFA. The findings indicated that SSS-WCMS has sufficient convergent and discriminant validity. The composite reliabil...
2020 IEEE 23rd International Multitopic Conference (INMIC), 2020
The rapid development of digital imaging and computer vision has extended the potential of using ... more The rapid development of digital imaging and computer vision has extended the potential of using these technologies in the diagnosis of human diseases. Medical image analysis is a non-invasive way to identify human diseases which are usually manually marked by medical experts or automatically detected by the Computer-Aided Diagnostic (CAD) system. The fundus images provide facts and information about visual disorders (diabetic retinopathy, glaucoma, age-related macular degeneration, etc.), brain disease (Alzheimer's), and heart-related diseases (cardiovascular, hypertension, and stroke). Extensive research has been done in the last two decades in developing automated methods for the identification of various human disorders from fundus images. This survey paper provides the reader with a broad review of the fundus image processing for the identification of various human disorders. In this paper, human diseases that can be diagnosed through fundus images are reviewed. Several publicly available fundus datasets which are helpful in the screening of these abnormalities are briefly discussed. This work aims to show the importance of retinal images in the diagnosis of different human diseases. The main challenges and difficulties faced in effective diagnosis are presented and discussed. We believe that this work will guide the researchers in addressing the challenges in existing solutions and assist doctors in the proper diagnosis of various diseases.
Optic Disc (OD) recognition is a fundamental phase in the developing methods for automated analys... more Optic Disc (OD) recognition is a fundamental phase in the developing methods for automated analysis of different chronic ocular disorders. In this article, a novel 46 Khan Bahadar Khan et al. technique has been introduced for OD detection and borderline extraction, which can be witnessed as a milestone in the advancement of a Computer-Assisted Diagnostic (CAD) framework for glaucoma detection in fundus photographs. A unique solution has been presented for removal of illuminated light spots due to refraction of camera light (so called fringe noise) on the edges of the retinal color images, which leads to false detection of OD. An intelligent non-uniform mixing of red and green channels is introduced for denoising of retinal photographs because of the dissimilar noise level in each channel. Template based matching technique is applied for OD localization of retinal image. The approach is thoroughly verified on openly accessible the DRIVE and the STARE datasets for OD detection and denoising of retinal images. This denoising technique greatly improved the accuracy of OD detection in contrast to other contending approaches.
In laparoscopic surgery, image quality is often degraded by surgical smoke or by side effects of ... more In laparoscopic surgery, image quality is often degraded by surgical smoke or by side effects of the illumination system, such as reflections, specularities, and non-uniform illumination. The degraded images complicate the work of the surgeons and may lead to errors in image-guided surgery. Existing enhancement algorithms mainly focus on enhancing global image contrast, overlooking local contrast. Here, we propose a new Patch Adaptive Structure Decomposition utilizing the Multi-Exposure Fusion (PASD-MEF) technique to enhance the local contrast of laparoscopic images for better visualization. The set of under-exposure level images are obtained from a single input blurred image by using gamma correction. Spatial linear saturation is applied to enhance image contrast and to adjust the image saturation. The Multi-Exposure Fusion (MEF) is used on a series of multi-exposure images to obtain a single clear and smoke-free fused image. MEF is applied by using adaptive structure decomposition...
Retinal vessel segmentation (RVS) is a significant source of useful information for monitoring, i... more Retinal vessel segmentation (RVS) is a significant source of useful information for monitoring, identification, initial medication, and surgical development of ophthalmic disorders. Most common disorders, i.e., stroke, diabetic retinopathy (DR), and cardiac diseases, often change the normal structure of the retinal vascular network. A lot of research has been committed to building an automatic RVS system. But, it is still an open issue. In this article, a framework is recommended for RVS with fast execution and competing outcomes. An initial binary image is obtained by the application of the MISODATA on the preprocessed image. For vessel structure enhancement, B-COSFIRE filters are utilized along with thresholding to obtain another binary image. These two binary images are combined by logical AND-type operation. Then, it is fused with the enhanced image of B-COSFIRE filters followed by thresholding to obtain the vessel location map (VLM). The methodology is verified on four differen...
Environmental Science and Pollution Research, 2021
The pro-poor growth and environmental sustainability are the twin agendas widely discussed in env... more The pro-poor growth and environmental sustainability are the twin agendas widely discussed in environmental science literature. The technology-embodied growth helps to attain both agendas through knowledge sharing and technology transfer, which trickle down to the poor income group and improve their living standards. Hence, the role of information and communication technologies (ICTs) is deemed crucial in boosting economic growth and is under deep consideration to establish its role in reducing poverty and environmental pollution. The current study examines the long-run relationship between ICTs, poverty reduction, and ecological degradation in Pakistan using time series data from 1975–2018. The short- and long-run parameter estimates were obtained through the Autoregressive Distributed Lag (ARDL) model for robust inferences. The results substantiate the inverted U-shaped Environmental Kuznets Curve relationship between income and emissions with a turning point at US$1000 in the short-run and US$800 in the long-run. The results confirmed the decisive intervention of ICTs factors in the poverty reduction, i.e., computer communications and mobile-telephone-broadband subscriptions support to reduce poverty incidence with the mediation of inbound FDI in a country. As far as income inequality is concerned, it shows that computer services support minimizing income inequality via a channel of high–technology exports in a country. The technology embodied emissions verified in the long-run, where mobile-telephone-broadband subscriptions increase carbon emissions. Finally, mobile-telephone-broadband subscriptions and inbound FDI both are significant contributors to amplify the country’s economic growth. The results conclude that poverty reduction and environmental sustainability agenda are achieved by developing green ICT infrastructure in a country.
The role of natural resources in promoting economic and financial activities is important for att... more The role of natural resources in promoting economic and financial activities is important for attaining country's economic growth. The study used different natural resource rents, domestic investment, trade openness, per capita income and their resulting impact on financial development in order to assess 'financial resource curse' hypothesis in Pakistan by using a consistent time series data from 1975 to 2017. The study employed ARDL-Bounds testing approach that is fairly worked under different order of integrated variables and displayed short-and long-run parameter estimates. Further, the study used VAR decomposition analysis to generate Impulse Response Function (IRF) and Variance Decomposition Analysis (VDA) to assessed forecasted variance and error shocks over a next 10 year time period. The results show that, in the short-run, initial level of forest rents and oil rents supported the 'natural resource abundance' hypothesis, as both the rents substantially increases country's financial development, however, in the long-run, there is a negative relationship of coal rents, forest rents, natural gas rents, and oil rents with domestic credit to private sector (DCPS), which confirmed the 'natural curse hypothesis' in a country. The domestic investment in the form of gross fixed capital formation (GFCF) largely supported the financial activities with all given resource rents in the models, while country's per capita income unable to signify its positive impact on DCPS under the resource curse environment during the study time period. The other results show that coal rents and oil rents decreases broad money supply whereas natural gas rents decreases market capitalization to validate 'financial resource curse' hypothesis in a country. The results of IRF and VDA approach confirmed the viability of both the competing natural resource theories (i.e., financial resource curse and financial resource blessing hypothesis) under financial development in the next 10 year time period.
Oat is an economically important crop and ranks sixth in world cereal production after maize, whe... more Oat is an economically important crop and ranks sixth in world cereal production after maize, wheat, rice, barley and sorghum. It has been primarily utilized as livestock feed. However, the utilization of oats for human consumption has increased progressively, owing to its dietary and health benefits which relies mainly on the total dietary fibre and β-glucan content, which significantly reduces postprandial blood glucose, insulin and blood lipids, especially serum total and low density lipoprotein cholesterol. Henceforth, enhancing Oat b-glucan content forhuman consumption is desirable. As it is a polygenic trait controlled mainly by genes with additive effects, phenotypic selection for greater b-glucan content would be effective for developing cultivars with elevated b-glucan contents. Oat b-glucan concentration has been found to be positively correlated with protein content and negatively correlated with oil content. β-glucan yield (i.e., Product of grain yield and β-glucan conte...
The visual exploration of retinal blood vessels assists ophthalmologists in the diagnoses of diff... more The visual exploration of retinal blood vessels assists ophthalmologists in the diagnoses of different abnormalities of the eyes such as diabetic retinopathy, glaucoma, cardiovascular ailment, high blood pressure, arteriosclerosis, and age-related macular degeneration. The manual inspection of retinal vasculature is an extremely challenging and tedious task for medical experts due to the complex structure of an eye, tiny blood vessels, and variation in vessels width. Several automatic retinal vessels extraction techniques have been proposed in contemporary literature, which assist ophthalmologists in the timely identification of an eye disorders. However, due to the fast evolution of such techniques, a comprehensive survey is needed. This survey presents a comprehensive review of such techniques, strategies, and algorithms presented to date. The techniques are classified into logical groups based on the underlying methodology employed for retinal vessel extraction. The performance of existing techniques is reported on the publicly accessible datasets in term of various performance measures, providing a valuable comparison among the techniques. Thus, this survey presents a valuable resource for researchers working toward automatic extraction of retinal vessels.
The crowd phenomenon frequently occurs in dense urban living environments. Crowd counting or esti... more The crowd phenomenon frequently occurs in dense urban living environments. Crowd counting or estimation helps to develop management strategies such as designing safe public places and evacuation plan for emergencies. These strategies are different depending upon the type of event such as political and public demonstrations, sports, and religious events. However, estimating the number of people in crowds at closed or open environments is quite challenging because of the dynamics involved in the process. In addition, crowd estimation itself poses challenges due to randomness in crowd behavior, motion, and an area’s geometric specifications. Crowd behavior as well as the area parameters is studied before suggesting any possible technological solution for managing a crowd. This article presents a theoretical understanding of the major crowd size estimation approaches that cannot be achieved through the study of existing survey papers in this area, because the existing survey papers focu...
It is now widely recognized that knowledge assets and technological enhancements are essential st... more It is now widely recognized that knowledge assets and technological enhancements are essential strategic resources for any organisation to achieve competitive advantage and sustainability. The imperative for achieving this efficiency is in transfer of relevant information for decision-making across all levels of company structure. It can be done with well-disposed knowledge management system, that improves the overall corporate performance. This paper examines how companies in Czech Republic manage their internal knowledge associated with environmental sustainability so as to improve their overall corporate performance.
Diabetic Retinopathy (DR) harm retinal blood vessels in the eye causing visual deficiency. The ap... more Diabetic Retinopathy (DR) harm retinal blood vessels in the eye causing visual deficiency. The appearance and structure of blood vessels in retinal images play an essential part in the diagnoses of an eye sicknesses. We proposed a less computational unsupervised automated technique with promising results for detection of retinal vasculature by using morphological hessian based approach and region based Otsu thresholding. Contrast Limited Adaptive Histogram Equalization (CLAHE) and morphological filters have been used for enhancement and to remove low frequency noise or geometrical objects, respectively. The hessian matrix and eigenvalues approach used has been in a modified form at two different scales to extract wide and thin vessel enhanced images separately. Otsu thresholding has been further applied in a novel way to classify vessel and non-vessel pixels from both enhanced images. Finally, postprocessing steps has been used to eliminate the unwanted region/segment, non-vessel pi...
Several empirical piece of research work illustrated that predicting effect of social support on ... more Several empirical piece of research work illustrated that predicting effect of social support on psychological wellbeing. But predicting effect of social support on psychological wellbeing is lacking in Indian perspectives. The purpose of current research work is to examine the predicting effect of social support on psychological wellbeing. Employed stratified disproportional random sampling technique 200 elderly within the age range of 60 to 70 years were selected from Chhattisgarh State. Correlational research design was employed in present research work. Psychological wellbeing was assessed by PGI general wellbeing questionnaire (Verma & Verma, 1989). Social support was assessed by self developed social support questionnaire. Predicting effect was examining by hierarchal regression analysis. Control factors (socio-demographic factors) explained 18% of total variance (R2=.180; F (5, 194) = 100.250; p<0.01). Social support explained an additional 20% (F (1,193) = 35.121, p<0....
Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer, Jan 6, 2015
The present study was designed to validate the Hindi version of the Multidimensional Fatigue Inve... more The present study was designed to validate the Hindi version of the Multidimensional Fatigue Inventory-20 (MFI-20) in Indian oncology population. The original English version of the MFI-20 was translated into Hindi (hMFI-20) using the translation and back translation processes. The hMFI-20 was administered to 200 cancer patients. The item analysis for hMFI-20 was carried out using the corrected item-total correlation. The confirmatory factor analysis (CFA) was employed to test whether the original factor structure of MFI-20 is confirmed for the hMFI-20. Further, convergent and discriminant validities were also tested. The reliability of the hMFI-20 was evaluated by computing composite reliability and Cronbach's α coefficient. Corrected item-total correlation value for each of the items of hMFI-20 was greater than 0.6. Results of the CFA (comparative fit indices (CFI) = 0.91, root mean squared residual (RMR) = 0.04, root mean square error of approximation (RMSEA) = 0.028, and χ (...
This study is a piece of empirical research work which aims to examine the prediction effect of o... more This study is a piece of empirical research work which aims to examine the prediction effect of organizational attractiveness on employee retention. Following the incidental cum random sampling technique 200 State bank of India (III class) employee were drawn from Chhattisgarh state to serve as participants in the present research work. In the present research work correlational research design was employed. Organizational attractiveness was measured by organizational attractiveness scale (Highhouse et. al., 2003). Employee retention was measured by employee retention questionnaire . Prediction effect was examining using by hierarchical regression analysis. The result of the present study indicates that in organizational attractiveness emerged as a significant predictor of employee retention. There is sufficient empirical and statistical evidence of the prediction effect of organizational attractiveness on employee retention in state bank of India III class employee.
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