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Diabetic Retinopathy Diagnosis Using Retinal Fundus Images through MobileNetV3
Diabetic Retinopathy (DR) is a major disease throughoutthe world. Diagnosis of diabetes at an early stage is so critical and could help save several lifestyles. One out of two individuals experiencing diabetes has been determined to have some phase of DR. Recognition of DR symptoms in time can turn away the vision weakness inmost the cases, nonetheless, such disclosure is troublesome with present devices and strategies. Existingmethods for determining whether a person is suffering from diabetes or maybe the chances of acquiring diabetesrely heavily on examiners. Most of the time, it can be treated if caught during the early stages. There is a need for creating models that are efficient and robust to detect DR holistically. In recent times the advent of Deep learning models has been used extensively in various Bio medical applications. In this work, we utilize a Hyper parameter tuned MobileNet-V3 model based on a multi-stage Convolutional Neural Network (CNN) to efficiently classify images from the IRDID dataset. A Multiclass classification model involving images collated from various sources were trained, validated and tested for classification accuracy. The network was evaluated based on parameters and the network was able to achieve an accuracy of 88.6% 2023 IEEE. -
Diagnose Diabetic Mellitus Illness Based on IoT Smart Architecture
Obtaining a quick remote diagnosis of heart disease has proven problematic in recent days. To overcome such issues in e-Healthcare systems, Internet of Things (IoT) applications have been deployed using cloud computing (CC) approaches. There are still a number of disadvantages to using CC, including latency, bandwidth, energy usage, and security and privacy concerns. Fog computing (FC), a CC development, may be able to overcome these obstacles. DiaFog enabling remote users for real-time diagnosis of diabetic mellitus disease (DMD) has been proposed in this study, which is based on the combined ideas of IoT, cloud, and fog computing, as well as an ensemble deep learning (EDL) technique. The proposed system is trained with EDL approaches on the integrated dataset of two diabetes mellitus disease datasets (DMDDs), namely, Pima Indians Diabetes Dataset (PIDD) and Hospital Frankfurt Germany Diabetes Dataset (HFGDD), obtained from the UCI-ML and Kaggle repository, respectively, and the integrated dataset of these two. The suggested system has been used to demonstrate accuracy, precision, recall, F-measure, latency, arbitration time, jitter, processing time, throughput, energy consumption, bandwidth utilization, network utilization, scalability, and more. In the remote instantaneous diagnosis of diabetic patients, the integration of IoT-fog-cloud is useful. The results of the trials show the value of employing FC principles and their applicability for speedy diabetic patient remote diagnosis. PACS-key is describing text of that key PACS-key describing text of that key. 2022 Abhilash Pati et al. -
Diagnosis and prediction of iigps countries bubble crashes during brexit
We herein employ an alternative approach to model the financial bubbles prior to crashes and fit a log-periodic power law (LPPL) to IIGPS countries (Italy, Ireland, Greece, Portugal, and Spain) during Brexit. These countries represent the five financially troubled economies of the Eurozone that have suffered the most during the Brexit referendum. It was found that all 77 crashes across the five IIGPS nations from 19 January 2015 until 17 February 2020 strictly followed a log-periodic power law or other LPPL signature. They all had a speculative bubble phase (following the power law growth) that was then followed by a sudden crash immediately after reaching a critical point. Furthermore, their pattern coefficients were similar as well. This study would surely assist policymakers around the Eurozone to predict future crashes with the help of these parameters. 2021 by the authors. Licensee MDPI, Basel, Switzerland. -
Diagnosis of Autism Spectrum Disorder: A Review of Three Focused Interventions
Autism is a neurological developmental disorder that impacts a persons physical, social, and emotional behavior. This disorder develops over time and is characterized by social deficits and repetitive behavior. Although there is no cure for this disorder, an early diagnosis and intervention can do significant wonders and can help the subject to become active functioning members of the family and society. The aim of this study is to minimize the diagnostic period by finding an optimal diagnosis procedure from the existing diagnosis tools. The diagnosis of autism can be done in three ways: 1. clinical evaluation; 2. screening tools; 3. brain images. In this review paper, we have thoroughly gone through all three types of diagnostic procedures and found that there was no single diagnostic tool to confirm the disorder. We also found that the diagnosis period was too long. As the result of this review, we found an ASD diagnosis triad which helps to choose the right diagnosis procedure based on the subjects age which reduces the diagnostic period and helps to aid early diagnosis by eliminating the chaos in choosing the diagnostic tools. 2022, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. -
Diagnosis of compromised accounts for online social performance profile network
Proliferation of internet technologies has changed the way content is created and exchanged through the Internet, prompting expansion of online networking applications and administrations. Online networking empower creation and exchanged the clients produced content and design of a scope of Internet-based applications. This development is fueled by more administrations as well as by the rate of their adoption by the users. While determined spammers misuse the built up trust connections between account proprietors and their companions to proficiently spread malignant spam, auspicious discovery of traded off records is quite challenge, because of the fixed trust association among the administration suppliers, account proprietors, and their companions. The proposed paper depicts a novel method to notice the cooperated user account in systems like Facebook and twitter. Our novel scheme consists of statistical method of modelling and detected to identity accounts that behaves a sudden change along with detected the compromised accounts. This paper gives validation of these behavioral elements by gathering and dissecting genuine client clickstreams to an OSN site. Taking into account our estimation study, further devise every client's social behavioral profile (SBP) by joining its separate behavioral element measurements. We assess the capacity of social behavioral profiles in recognizing distinctive OSN clients, and the simulation results demonstrate the social behavioral profiles precisely separate every OSN clients and distinguish traded off records. 2016 IEEE. -
Diagnosis of Osteoporosis from X-ray Images using Automated Techniques
Osteoporosis is Bone Disease most commonly seen in aged people due to various food habits and life style habits. The bone becomes so brittle and weak which may break just from a fall. So, it is required to attend this Issue as there are various challenges faced by medical domain to identify and treat Osteoporosis. In this paper we focus on identifying and detecting osteoporosis using X-ray images using modified U-net Architecture using Residual Block and skip connections and done comparison study with existing models, as per state-of-art our model outcomes issues in existing model and obtain better accuracy. 2022 IEEE. -
Diagnosis of Retinal Disease Using Retinal Blood Vessel Extraction
The eye is one of the important organs of the human body. In recent times, major parts of the eye are damaged due to various retinal diseases. Major diseases related to the retina are glaucoma, papilledema, retinoblastoma, diabetic retinopathy, and macular degeneration. These diseases can be detected using image processing techniques. These diseases can cause damage to the eye; hence the early diagnosis can prevent the loss of vision. Thus the early stage of rectification may lead to smaller damage than the risky ones. By extracting the blood vessels, various retinal diseases can be identified, and the severity of the disease can also be identified. Some of these diseases in the retina will occur due to hypertension, blood pressure, and diabetics. Thus, the tear in the blood vessels leads to the loss of visuality in human beings. The proposed work consists of image processing techniques such as segmentation, feature extraction, and boundary extraction which lead to the identification of various retinal diseases with a certain level of accuracy, sensitivity, and specificity by using image processing techniques. The training and testing of retinal images are carried out by using the artificial neural network (ANN) classifier for glaucoma detection and support vector machine (SVM) classifier for detecting diabetic retinopathy. 2021, Springer Nature Switzerland AG. -
Diametral paths in total graphs of complete graphs, complete bipartite graphs and wheels
The diametral path of a graph is the shortest path between two vertices which has length equal to diameter of that graph. In raising of structures with columns and beams in Civil Engineering, determining of diametral paths is of great significance. In this paper, the number of diametral paths is determined in complete graphs, complete bipartite graphs, wheels and their total graphs. IAEME Publication. -
Diaspora Experience Between the Creation and the Creator : A Closer Look at the Diaspora Connected Character in Anita Desai's 'Fasting, Feasting'
Quest International Multidisciplinary Research Journal, Vol-1 (2), pp. 83-86. ISSN-2278-4497 -
Diazanorbornene: A Valuable Synthon towards Carbocycles and Heterocycles
Desymmetrization of meso compounds is well recognized as a powerful method for delivering biologically relevant molecular skeletons in a few synthetic steps. Heterobicyclic olefins are a class of meso compounds which exhibit exceptional reactivity due to their high ring strain originating from the unfavorable bond angles and eclipsing interactions. Extensive research was carried out towards the synthetic transformations of oxa-, aza-, and diazanorbornenes/norbornadienes for the synthesis of a wide variety of carbocycles and heterocycles in a single step, most importantly in a stereo- and chemo-selective manner. This review summarizes the relevant aspects of diazanorbornene reactivity which will inspire the synthetic community for exploiting these highly strained bicyclic systems for the creation of extensive libraries of novel structurally and biologically interesting molecules. The review is divided into several sections based on the type of reactions that diazanorbornenes are subjected to. 2020 Wiley-VCH GmbH -
Diazo-pyrazole analogues as photosensitizers in dye sensitised solar cells: Tuning for a better photovoltaic efficiency using a new modelling strategy using experimental and computational data
The designing of a dye sensitised solar cell (DSSC) is one of the frontiers in harvesting solar energy as it provides an alternative to economic photovoltaic devices with increased efficiency. In this manuscript, we report a new methodology using experimental and theoretical data for the evaluation of the photosensitiser activity of organic dyes using theoretical simulations and experimental cell efficiency data. As a representative example, we designed a series of 54 novel pyrazole derivatives which are subjected to TD-DFT simulations (CAM-B3LYP/6-311G++ (2d, p)) and photovoltaic modelling. Data from computational simulations, as well as known experimental cells, are used for the calculation of photovoltaic efficiency. We selected pyrazole derivatives because of its proven use in DSSC as an effective dopant in a blended polymer electrolyte in nanocrystalline DSSC. Fine-tuning with the effect of substitution and with the ?spacers at the ortho, meta and para positions for -OCH3, -OH, -CHO, -NO2 respectively were done. Enhanced efficiency of 7.439% was observed as compared to the standard cell of efficiency of 5.530%. An increase in efficiency was not observed with the effect of ?spacers. The newly designed dyes demonstrate desirable energetic and spectroscopic parameter that can lead to efficient metal-free organic dye sensitiser for DSSC's. The main advantage of this strategy is the incorporation of both simulated and experimental data. It will reduce the possible errors from the simulations and also, helps in performing time-consuming experimental studies. 2020 Walter de Gruyter GmbH, Berlin/Boston. -
Dictionary-Based BPT Compression with Trimodal Encryption for Efficient Fiber-Optic Data Management and Security
Fiber-optic transmission systems are capable of carrying tens of terabits per second of traffic and thereby form the core infrastructure for all Internet-based services and applications. While fiber-optic communication provides rapid data transfer, it faces the challenge of managing the substantial data volumes generated, stored, or transmitted. In the realm of fiber-optic communication, data interception is straightforward, necessitating robust security measures. One effective solution is compression-based encryption, which combines security with data compression benefits. Encryption safeguards data by transforming it into ciphertext during transmission, rendering it unreadable to attackers without knowledge of the encryption method. Data compression enhances bandwidth efficiency, enabling the efficient transmission of large data volumes using limited bandwidth. In the event of data compromise, attackers must grasp both compression and encryption methods to decipher the information, adding an additional layer of security. In this paper, an encoding technique named the Bounded Probability-Based Textual Data Compression (BPT) algorithm is introduced with trimodal encryption method for securing the short textual data while transferring from source to the destination. The BPT algorithm creates a codeword using a dictionary that assigns binary codes according to character occurrence probabilities in the input data. To decompress, the coding table must be transmitted alongside the compressed data. The trimodal encryption is used as a second tier for securing the data that was compressed using BPT algorithm. The trimodal encryption employs three encryption methods, and data is encrypted using one of these methods during transmission to the destination. The BPT algorithms performance is evaluated using benchmark textual datasets from the Calgary Corpus and the Canterbury Corpus. The experimental results demonstrate the unique characteristics of the BPT algorithm, including compression ratio (CR), compression factor (CF), bits per character (BPC), and space savings. Additionally, the Trimodal encryption algorithm (TME) method is evaluated using end-to-end delay analysis, packet loss analysis, and packet delivery ratio assessment. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
Did Russia's Invasion of Ukraine Induce Herding Behavior in the Indian Stock Market?
This study empirically examines the herding behavior of the Indian stock market investors during the heightened geopolitical tensions between Russia and Ukraine in 2022. An intensified Russia-Ukraine geopolitical event window was constructed, and the high-frequency trading data (intraday) of the Nifty index was analyzed using Multifractal Detrended Fluctuation Analysis (MFDFA) to compute the 5th-order Hurst exponent (Hq (5)) that detects herding behavior. The study's empirical results revealed the presence of profound herding behavior during the intensified Russia-Ukraine geopolitical event window. The study contributes to the existing literature on herding behavior by examining the impact of a geopolitical event on the Indian stock market. Additionally, the study utilizes MFDFA to compute Hurst exponents, a relatively new approach to detecting herding behavior in financial markets. The findings of this study may assist investors and policymakers in understanding the impact of geopolitical events on financial markets and the potential for herding behavior among investors during times of heightened uncertainty. The study's results demonstrate the interconnectedness of global events and financial markets, highlighting the need for policymakers to consider the potential social and economic consequences of geopolitical events. 2023 The Author(s). -
Did the Economic Reforms Change the Macroeconomic Drivers of the Indian Economy in the Post-Reform Era? An ARDL Bounds Test Approach
Purpose: The purpose of this study is to investigate the macroeconomic forces that have been driving the Indian economy during both the pre-reform and post-reform eras, that is, from 1950-1951 to 1990-1991 and from 1991-1992 to 2022-2023 respectively. Problem: The Indian economy underwent significant economic and financial sector reforms in 1991-92, with the goal of reviving its stagnant growth. These reforms are intended to spur the economic growth of India. What were the main forces behind the Indian economy before and after the reforms? Is the research question. The goal of the current study is to determine if the economic reforms shifted or maintained the pre-reform eras driving forces for the Indian economy in the post-reform era. Design/Methodology/Approach: The gross domestic product (GDP), the gross domestic savings (GDS), the private consumption expenditure (PFCE), the government final consumption expenditure (GFCE), the inflation rate, the exchange rate, the exports, the imports, the internal and external borrowings of the government, personal remittances, foreign direct investment (FDI), and foreign portfolio investments (FPI) are all taken into consideration in order to fill the research gap that has been identified as a result of the comprehensive review of the literature. Following an analysis of the selected variables' fundamental characteristics, an econometric model is developed using the Autoregressive Distributed Lag (ARDL) Bounds Test Model. Findings: There is no evidence of long-run causation and association between the variables, but the findings of the ARDL Bounds Test showed that in the pre-reform period, PFCE is the major driver of the GDP in the short-run, with strong support from imports. However, since the reform, PFCE, GDS, and Exports are the primary short-and long-term contributors to GDP. Practical Implication: These findings indicate that India's macroeconomic system is shifting. The Indian economy has undergone a dramatic shift, moving away from a reliance on imports and toward one that is consumer-driven and export-driven. As savings and consumer expenditures are the main drivers of the Indian economys growth in the post-reform era, policies should be designed to increase savings and consumption as well as increase exports. 2023, ASERS Publishing House. All rights reserved. -
Did the selected economic variables impact the inflation and GDP growth of India during 1990-2016? /
Sumedha Journal of Management, Vol.7, Issue 3, pp.1-21, Print ISSN No. 2277-6753. Online ISSN No. 2322-0449. -
Didacticism in popular bollywood films: A study on Raikumar Hirani's directional films /
The dissertation titled “Didacticism in Popular Bollywood Films: A Study on Rajkumar Hirani's Directorial Films,” speaks about the representation of didactic elements in popular Bollywood films. Didacticism is a philosophy that has been employed in various artistic endeavours from time before the Ancient Greeks. This philosophy believes that any piece of literature or art are meant to both entertain and educate. Popular cinema is also an artistic medium and has the ability to attract a number of people. Popular Bollywood Cinema helps us to understand a lot about the culture and lifestyle of the people. -
Dielectric performance of graphene nanostructures prepared from naturally sourced material
Cost-effective and environmentally benign approach was adopted for the synthesis of oxidized graphene nanostructures from the precursor coke via Improved Hummers' method. The surface states of oxygen functional groups provided strong polarization for enhanced dielectric properties. Occurrence of dipole and interfacial polarizations in the low frequency region contributed to the dispersive behaviour of ?', ?", and tand.The relaxation phenomenon of the structure lead to an augmented electrical conductivity with increase in frequency. Our finding reveals the advantageous fabrication of graphene nanostructure having high dielectric constant (1 0 5) but with low loss which can be used in advanced nanodielectrics. 2020 Elsevier Ltd. All rights reserved. -
Dielectric performance of solid dielectric immersed in vegetable oil with antioxidant
Transformers are the most vital part of the power transmission and distribution system. Protecting them from all possible abnormalities is of very high priority. The insulation levels in the transformers need to be of very high grade as the power and voltage levels of a transformer are very high. Transformers are generally filled with petroleum based mineral oil as an insulator and also as a coolant inside them. These oils are highly inflammable and also highly toxic. They are also non-biodegradable, causing major harm to the environment. Vegetable oils which are abundant in nature unlike the mineral oil is being studied as a suitable substitute for mineral oils as transformer oil. The availability of vegetable oils differ from place to place. The work here focusses on the commercially available vegetable oils in India. Seven different samples of oil are tested for their dielectric properties and viscosity and the best one among them is tested with a solid dielectric (epoxy) immersed within it in order to simulate more appropriate conditions of a practical transformer. The tests are conducted based on Indian Standards (IS6792). 2016 IEEE. -
Dietary nutrients and their control of the redox bioenergetic networks as therapeutics in redox dysfunctions sustained pathologies
Electrons exchange amongst the chemical species in an organism is a pivotal concomitant activity carried out by individual cells for basic cellular processes and continuously contribute towards the maintenance of bioenergetic networks plus physiological attributes like cell growth, phenotypic differences and nutritional adaptations. Humans exchange matter and energy via complex connections of metabolic pathways (redox reactions) amongst cells being a thermodynamically open system. Usually, these reactions are the real lifeline and driving forces of health and disease in the living entity. Many shreds of evidence support the secondary role of reactive species in the cellular process of control apoptosis and proliferation. Disrupted redox mechanisms are seen in malaises, like degenerative and metabolic disorders, cancerous cells. This review targets the importance of redox reactions in the body's normal functioning and the effects of its alterations in cells to obtain a better understanding. Understanding the redox dynamics in a pathological state can provide an opportunity for cure or diagnosis at the earlier stage and serve as an essential biomarker to predict in advance to give personalized therapy. Understanding redox metabolism can also highlight the use of naturally available antioxidant in the form of diet. 2021 Elsevier Ltd -
Dietary Plants, Spices, and Fruits in Curbing SARS-CoV-2 Virulence
Patients with coronavirus disease 2019 (COVID-19) infection can suffer from a variety of neurological disorders; therefore, there is a demand to investigate specific treatments. As a part of this endeavor, academic databases related to clinical, neuropathological, and immunological biomarkers were examined for searching promising drugs to treat neurological disorders in the COVID-19 group. Also, the neuroprotective potential of herbs for patients with post-COVID-19 has been evaluated using PubMed, MEDLINE, Scopus, EMBASE, Google Scholar, EBSCO, Web of Science, Cochrane Library, WHO database, and ClinicalTrials.gov. The terms used for the Boolean search were Indian herbs and neuroprotective potential, post-COVID-19 symptoms, and so on. Based on our knowledge, nervous system immunity is an inherent characteristic of the nervous system because it is highly immunologically active. It was found that patients infected with COVID-19 often experience neurological symptoms such as muscle pain, headaches, confusion, dizziness, and loss of smell and taste. The most commonly used herbs for neurological disorders are Bacopa monnieri, Mucuna pruriens, Withania somnifera, Acorus calamus, Phyllanthus emblica, Blumea balsamifera, Asparagus racemosus, Cannabis sativa, Convolvulus prostratus, Swertia chirata, Vitex negundo, Nyctanthes arbor-tristis Linn, Centella asiatica, Curcuma longa, Ocimum tenuiflorum. It is widely recognized that herbal drugs have the potential for treating neurological diseases such as Parkinsons, Alzheimers, and cerebrovascular diseases in COVID-19 patients. However, clinical trials are still limited. The suitability of drugs depends on the investigation of biomarkers and pathobiological mechanisms. Thus, it is necessary to use modern scientific approaches and technologies to conduct comprehensive mechanistic studies to understand the therapeutic potential of herbs for neurological disorders associated with the SARS-CoV-2 infection. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.