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A primary study on the degradation of low-density polyethylene treated with select oxidizing agents and starch
Polyethylene has become an integral part of our contemporary lives. The neoteric versatile nature of polyethylene is used in constructing various applications. Out of the plastic waste discarded, 60% of the plastic waste enters landfills. The polyethylene discarded in the soil and water on exposure to the environment forms macroplastics (>2.5 cm), mesoplastics (5 mm-2.5 cm) and microplastics (<5 mm). Microplastics in the water and soil are observed to have lethal and ecotoxicological effects on aquatic and terrestrial organisms. They enter the food chain and permeate into the food that one eats. In order to address this impending concern, the present study aimed to treat plastics to form a degradable, safe and earthy material. The dissolved polyethylene was treated with starch and was made to react with oxidizing agents such as hydrogen peroxide, nitric acid and acetic acid to lower its inert ability to withstand its degradation. The effect of starch and oxidizing agents on dissolved low density polyethylene was subsequently analysed. The analysis of treated polyethylene showed a decrease in its crystallinity percentage by 6.19 and an increase in its functional groups on reaction with solvent trichloroethylene made to react with starch and oxidizing agents. In the present research, tests were conducted to obtain the various methods that can be utilized to reverse the inert ability of polyethylene. The prevailing recycling model that uses antioxidation techniques is counterproductive since it was found that such techniques appeared to make the polyethylene more resistant to further degradation. In this study, the polyethylene was dissolved in the solvents, such as xylene and trichloroethylene, to make the polyethylene more susceptible to reactants and hence a viable model for treating polyethylene. : Author (s). Publishing rights @ ANSF. -
A privatised approach in enhanced spam filtering techniques using TSAS over cloud networks
Major problem over cloud networks is the effect of malicious code that protrudes its own activity without intend of network user in resource sharing. One such activity is the spam-filtering techniques which assumes the data with training and testing sets and also rely on fundamental classification through distribution. A privatised spam filtering approach is a classic problem which automatically recognises user context and incoming mail information relevance. To filter mail contents learning based methods, probabilistic based method trying to improve their accuracy but they cannot attain an improvement in identifying suspicious contents and also in segregating legitimate mail entries. Here a novel representation of structured abstraction scheme (SAS) used to generate abstraction in e-mail process using HTML tag content in e-mail and its algorithm for filtering such process of spam filtering is depicted. In this SAS methodology near duplicate matching process with HTML tag ordering will be processed and newly assigned position ordering were deliberated. The experimental setup shows that there will be a great improvement while filtering spam in accuracy of e-mail content while sharing in cloud networks. Copyright 2022 Inderscience Enterprises Ltd. -
A probabilistic inference algorithm for early detection of age related macular degeneration
Age Related Macular Degeneration or ARMD is a retinal disorder that causes blindness over people of older age group. ARMD is associated with age and is a leading cause of blindness around the world. There is no specific medicine to fully cure ARMD but its development can be controlled by regular exercises and a healthy lifestyle if it is detected early. With a rising population of old age group of people, it becomes important to detect ARMD as early as possible in order to contain its development further. This research attempts to develop an algorithm based on probabilistic inference through Bayesian Network by analyzing large datasets collected from previous cases where datasets include elements of risk factors that could cause ARMD along with eye images. Unlike most of the approaches in detecting ARMD this work not only analyses eye images but also includes analysis of various factors causing the disorder. To include the study and analysis of the presence of factors causing ARMD is sensible because those factors are good indicators when the need is an early detection. 2020, Engg Journals Publications. All rights reserved. -
A process to beneficiate A-Alumina and magnesium aluminate composite powder /
Patent Number: 202141035837, Applicant: Parvati Ramaswany.
An environmentally friendly process to beneficiate a-alumina (AI2O3 - corundum) and magnesium aluminate (MgAbOj - spinel, linear formula: MgOAbOj) ceramic composite powder, from black aluminum dross (an industrial waste), has been disclosed. The process involves grinding of the Al-Dross, leaching of the undesirable compounds (A1N) by using hot carbonated water, dehydration and calcination, wherein the ammonia gas (whenever it was evolved) was scrubbed through dilute H2SO4. -
A process for synthesis of mixed carbon allotropes /
Patent Number: 201941052829, Applicant: CHRIST (Deemed to be University).
A process for synthesis of novel mixed carbon allotropes is disclosed. The process includes combusting liquid paraffin by a flame via wick; collecting liquid paraffin soot generated during the combustion. The as-harvested liquid paraffin soot comprises of novel mixed carbon allotropes namely H18 carbon and n-diamond blended with Carbon Nano Onions. -
A process for the synthesis of novel 6-(BENZO[D][1,3]DIOXOL-5-YL)-Pyrroles /
Patent Number: 202141037575, Applicant: Santhosh Govindaraju. Nitrogen-containing heterocycles are biologically significant structures present in many natural substrates and synthetic drugs. Pyrrole is one such member of the nitrogen heterocycle family consisting of a five-membered ring having a nitrogen atom. Pyrrole forms an integral part of many natural substances such as porphyrins and pigments. The discovery and synthesis of pyrrole derivatives.is an integral and interesting part of research by synthetic organic chemists all over the world. -
A process to fabricate plasma sprayed magnesium aluminate refactory coating from oxide powder beneficiated from black aluminium dross /
Patent Number: 202141055626, Applicant: Parvati Ramaswamy.
A process is described to synthesize magnesium aluminate (MgAl2O4 - spinel, linear formula: MgO-Al2O3) refractory coating that was obtained by plasma spray coating α-alumina (Al2O3 - corundum) and MgAl2O4 ceramic composite powder that was previously beneficiated from black aluminum dross, an industrial waste. The ceramic composite powder was converted into plasma sprayable powder by a combination of processes that included sieving and spray drying with optimized parameters. -
A Progressive UNDML Framework Model for Breast Cancer Diagnosis and Classification; [Un modelo marco progresivo UNDML para el diagntico y clasificaci del ccer de mama]
According to recent research, it is studied that the second most common cause of death for women worldwide is breast cancer. Since it can be incredibly difficult to determine the true cause of breast cancer, early diagnosis is crucial to lowering the diseases fatality rate. Early cancer detection raises the chance of survival by up to 8 %. Radiologists look for irregularities in breast images collected from mammograms, X-rays, or MRI scans. Radiologists of all levels struggle to identify features like lumps, masses, and micro-calcifications, which leads to high false-positive and false-negative rates. Recent developments in deep learning and image processing give rise to some optimism for the creation of improved applications for the early diagnosis of breast cancer. A methodological study was carried out in which a new Deep U-Net Segmentation based Convolutional Neural Network, named UNDML framework is developed for identifying and categorizing breast anomalies. This framework involves the operations of preprocessing, quality enhancement, feature extraction, segmentation, and classification. Preprocessing is carried out in this case to enhance the quality of the breast picture input. Consequently, the Deep U-net segmentation methodology is applied to accurately segment the breast image for improving the cancer detection rate. Finally, the CNN mechanism is utilized to categorize the class of breast cancer. To validate the performance of this method, an extensive simulation and comparative analysis have been performed in this work. The obtained results demonstrate that the UNDML mechanism outperforms the other models with increased tumor detection rate and accuracy. 2024; Los autores. -
A Prompt Study on Recent Advances in the Development Of Colorimetric and Fluorescent Chemosensors for Nanomolar Detection of Biologically Important Analytes
Fluorescent and colorimetric chemosensors for selective detection of various biologically important analytes have been widely applied in different areas such as biology, physiology, pharmacology, and environmental sciences. The research area based on fluorescent chemosensors has been in existence for about 150years with the development of large number of fluorescent chemosensors for selective detection of cations as metal ions, anions, reactive species, neutral molecules and different gases etc. Despite the progress made in this field, several problems and challenges still exist. The most important part of sensing is limit of detection (LOD) which is the lowest concentration that can be measured (detected) with statistical significance by means of a given analytical procedure. Although there are so many reports available for detection of millimolar to micromolar range but the development of chemosensors for the detection of analytes in nanomolar range is still a challenging task. Therefore, in our current review we have focused the history and a general overview of the development in the research of fluorescent sensors for selective detection of various analytes at nanomolar level only. The basic principles involved in the design of chemosensors for specific analytes, binding mode, photophysical properties and various directions are also covered here. Summary of physiochemical properties, mechanistic view and type of different chemosensors has been demonstrated concisely in the tabular forms. Graphical Abstract: In our current review we have focused the history and a general overview of the development in the research of fluorescent sensors for selective detection of various analytes at nanomolar level only. [Figure not available: see fulltext.] 2024, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature. -
A proof of concept implementation of a mobile based authentication scheme without password table for cloud environment
Cloud computing is a fast growing technology offering a wide range of software and infrastructure services on a pay-per-use basis. Many small and medium businesses (SMB's) have adopted this utility based Computing Model as it contributes to reduced operational and capital expenditure. Though the resource sharing feature adopted by Cloud service providers (CSP's) enables the organizations to invest less on infrastructure, it also raises concerns about the security of data stored at CSP's premises. The fact that data is prone to get accessed by the insiders or by other customers sharing the storage space is a matter of concern. Regulating access to protected resources requires reliable and secure authentication mechanism, which assures that only authorized users are provided access to the services and resources offered by CSP. This paper proposes a strong two-factor authentication mechanism using password and mobile token. The proposed model provides Single Sign-on (SSO) functionality and does not require a password table. Besides introducing the authentication scheme, the proof of concept implementation is also provided. 2015 IEEE. -
A Proposal of smart hospital management using hybrid Cloud, IoT, ML, and AI
There has been a rapid shift in the medical industry from the service point of view. More importance is being given to patient care and customer satisfaction than ever before. The need to keep the customers happy with the hospital's service has increased rapidly and one way they can improve a patient's experience, even more is if they integrate cloud, IoT, ML, and AI into their system. This would help the medical sector to achieve customization which would enable them to address the needs of their customers more efficiently and offering personalized solutions. In this paper, we are proposing a novel model which focuses on a smart hospital information management system that runs by using hybrid cloud, IoT, ML, and AI. This system would be beneficial not only from the hospitals perspective but also from the patient's side as well. Patients and doctors unique ID would make the entire process a lot more efficient and easier. The advances happening in the field of AI and ML due to cloud-based computing is extremely beneficial for the medical industry. By integrating these components along with IoT it is possible for multi-specialty hospitals and super specialty hospital to be able to set up a smart hospital information management system. 2019 IEEE. -
A proposed framework for an appropriate governance system to develop smart cities in India
The Government of India has undertaken a novel step towards building new smart cities as well as transforming some of its existing cities into smart cities. However, tension relating to the governance of smart cities has emerged. Therefore, a mixed-methods approach was used based on a perception survey, case studies, and discussions with stakeholders and experts, to examine the current governance challenges in transforming existing cities into smart cities, and to explore various perspectives to propose a framework for an appropriate governance system for developing smart cities in India. The findings suggested that the current executive-led governance system, with special-purpose vehicles (SPVs) under the control of the state governments as the promoters of smart city development, might not lead to the smart governance system envisaged but, rather, add confusion and conflict, and undermine the constitutionally mandated, legislative-led urban local bodies. The argument in this article is for a people-centric, balanced governance approach with strengthened urban local bodies, enabled by advanced digital technology and the constructive participation of different social solidarities, in which the SPVs would act as the intellectual and executive wing of the urban local bodies. 2023 Regional Studies Association. -
A proposed framework for crop yield prediction using hybrid feature selection approach and optimized machine learning
Accurately predicting crop yield is essential for optimizing agricultural practices and ensuring food security. However, existing approaches often struggle to capture the complex interactions between various environmental factors and crop growth, leading to suboptimal predictions. Consequently, identifying the most important feature is vital when leveraging Support Vector Regressor (SVR) for crop yield prediction. In addition, the manual tuning of SVR hyperparameters may not always offer high accuracy. In this paper, we introduce a novel framework for predicting crop yields that address these challenges. Our framework integrates a new hybrid feature selection approach with an optimized SVR model to enhance prediction accuracy efficiently. The proposed framework comprises three phases: preprocessing, hybrid feature selection, and prediction phases. In preprocessing phase, data normalization is conducted, followed by an application of K-means clustering in conjunction with the correlation-based filter (CFS) to generate a reduced dataset. Subsequently, in the hybrid feature selection phase, a novel hybrid FMIG-RFE feature selection approach is proposed. Finally, the prediction phase introduces an improved variant of Crayfish Optimization Algorithm (COA), named ICOA, which is utilized to optimize the hyperparameters of SVR model thereby achieving superior prediction accuracy along with the novel hybrid feature selection approach. Several experiments are conducted to assess and evaluate the performance of the proposed framework. The results demonstrated the superior performance of the proposed framework over state-of-art approaches. Furthermore, experimental findings regarding the ICOA optimization algorithm affirm its efficacy in optimizing the hyperparameters of SVR model, thereby enhancing both prediction accuracy and computational efficiency, surpassing existing algorithms. The Author(s) 2024. -
A prospective study on portrayal of rural theme in selected Tamil films /
Tamil film industry is popularly known as Kollywood. It has its own unique elements which makes it different from other film industry in Indian cinema. The researcher has tried to find out if there is any kind of rural element in the films which she has chosen in chronological manner. The researcher has analyzed based on certain concrete parameters. -
A protoberberine alkaloid based ratiometric pH-responsive probe for the detection of diabetic ketoacidosis
Herein we report a ratiometric naturally occurring fluorescent pH probe, berberrubine (BBn) for the direct detection of diabetic ketoacidosis (DKA) conditions of patients having type I diabetes mellitus. The photophysical properties of the probe during pH titrations showed remarkable changes in absorption spectra where two absorption bands at 377 and 326 nm have disappeared followed by the emergence of an absorption maxima at 346 nm in highly acidic conditions. In addition, a fluorescence enhancement effect was observed in the alkaline pH, with a bathochromic shift of 33 nm. Moreover, the solution switches the color from light yellow to light pink with the change of pH from acidic to basic. A pKa value of 7.57 and a good linearity between pH 5.09.0 indicate that the probe can be used efficiently for the DKA condition, where pH variations are in the range of 67. The excellent water solubility, photostability, reversibility, and selectivity of BBn make it a potential pH sensing agent for acidic microenvironments. The reversible sensing of pH variations during DKA could be effective in primary detection and diagnosis which can assist in avoiding further complications of acidosis. 2021 Elsevier Ltd -
A Psychoanalytical Deconstruction of Surpanakha in Kavita Kane's Lanka's Princess
This paper endeavours to examine the character Surpanakha in Kavita Kane's novel Lanka's Princess. It attempts to critically follow her struggle in the androcentric space with the trapping of being a female. Breaking down her identity as a daughter, sister, wife and more specifically, as an individual, it tracks down the formulation of her own self-perception in order to reinterpret her femininity. Through the psychoanalytical lenses, this work also critically analyses her 'repression, rage and revenge' by connecting the dots in her journey that shape her personality. The giving of voice to the 'unvoiced' through revisionist myth making in the novel and the evolution of 'Surpanakha' from 'Meenakshi' due to her experiences in the oppressive and suffocating environment is the focal point of the paper. Keywords 2021 Copyright 2021 by Koninklijke Brill NV, Leiden, The Netherlands. -
A psychoanalytical study of surrealist elements in films /
Psychoanalysis has over the years been a centre of attraction and intense research and study by critiques, psychologists, sociologists, etc. due to its unique outlook at the world, Freud’s psychoanalytical theories have found their way onto films, which use the creativity of visuals, sounds, effects etc to create the world Freud claims to be hidden behind the human consciousness. No film can escape psychoanalysis as it frames the underlying reasoning behind human behavior and thus this forms a most intriguing realm of study. -
A psychoanalytical study of the nature and appearance of character analysing 6 songs each of Jim Morrison, Kurt Cobain and Janis Joplin (members of the famous club 27) /
To understand how character could be understood by analysing the greatest works of the above artists. This research is to find a possible connection to show that the songs written by the artist is not just a form of expression but also to show the world who they are, and their ideologies and most importantly what they feel about themselves. -
A Psychological Analysis of the Structural, Socio-Cultural, And Legal Aspects of Women's Rights, their Societal Development & Superstition-Gender-Based Violence and their Eradication Alarming Practice
This comparative analysis examines the phenomenon of witch hunting as an organized crime against women in India. It explores the similarities between witch hunting and organized crime, shedding light on the structural, socio-cultural, and legal aspects of this alarming practice. The analysis delves into the systematic targeting of women, the role of patriarchal power dynamics, economic motivations, legal frameworks, and the profound impact on victims. This exploration aims to enhance understanding of the complex dynamics surrounding witch-hunting as an organized crime against women in the Indian context. Witch-hunting, a deeply rooted, superstition-based practice continues to plague several regions of India. This practice has fostered another category of gender-based violence, making women the primary victims of witch-hunts over time. The paper delves into the prevalent issue of witch-hunting, focusing on its organized nature and thus, drawing a synonymity between witch-hunts and organized crimes. The paper also aims to analyze the various factors contributing to the organization of witch-hunting and its implications on women's rights and societal development. By examining historical contexts, cultural beliefs, socio-economic factors, and legal frameworks, this research seeks to shed light on the complex nature of this crime and propose strategies for its eradication. 2023, Journal for ReAttach Therapy and Developmental Diversities. All Rights Reserved. -
A PV-Powered Single Phase Seven-Level Invertera's Photocurrent and Injected Power
The PV inverter in this study is linked to the grid and its performance analysis is evaluated using a PI controller. It is a single phase multi-level PV inverter. The major objective of this research is to increase efficiency and eliminate harmonics caused by DC link voltage fluctuations created by Maximum Power Point Tracking (MPPT) during foggy situations. PV inverters generate and inject actual power into the main grid. This study uses a transformer-less photovoltaic inverter to cut down on losses, cost, and size. A transformer-less multilayer inverter is described in this paper. There is no high-frequency leakage current since that inverter can distribute both actual and reactive electricity. MATLAB/Simulink software was used to analyze and assess the effects of various PV-based seven-level techniques on the devicea's Maximum Power Point Tracking (MPPT) performance. The Authors, published by EDP Sciences, 2024.