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Solid state, rapid mechanochemical route for TiO2 coated Schiff-base polymer as adsorbent for the exclusion of hexavalent Cr from water
The removal of hexavalent Cr from water is vital considering its harmful and carcinogenic effects on human health as well as the environment. Effective exclusion of Cr(VI) provides reliable water to consume, impedes bioaccumulation, and mitigates environmental pollution. The present work details the rapid, ecofriendly, solvent-free mechanochemical route for the development of a polymeric Schiff-Base-wrapped TiO2 (SBP@TiO2) nano-adsorbent for the effective removal of Cr(VI) from water. The comprehensive understanding of the structural and chemical characteristics of the newly synthesized materials were examined through Fourier transform infrared (FTIR) spectroscopy, X-Ray Diffraction (XRD), and Scanning electron microscopy (SEM) with energy dispersive X-ray (EDX) spectroscopy. To assess the adsorption capacity, kinetics, and equilibrium of Cr(VI) adsorbate on adsorbent material (TiO2 and SBP@TiO2) and to understand the interplay between the critical parameters and their impact on adsorption, a series of batch adsorption studies were carried out. The adsorption equilibrium data for the Cr(VI) adsorption process fitted well with the Freundlich isotherm model of adsorption and adsorption kinetics disclosed that the data are in excellent agreement with R2 values of 0.98721 for the pseudo-second-order, indicating that the sorption process is by chemisorption. Thermodynamic measurements revealed that the adsorption of Cr(VI) on SBP@TiO2 was spontaneous and endothermic, as corroborated by the ?ve value of ?Go and the +ve value of ?Ho, respectively. It was discovered that the sorption of 10 and 50 ppm of Cr(VI) on SBP@TiO2 was 96% and 75.4% under optimal conditions, respectively. In contrast, the sorption study of Cr(VI) on TiO2 under identical conditions was found to be 49%. The study found that surface functionalization of TiO2 by SBP admirably improved the adsorption capacity, signifying SBP@TiO2 as an efficient Cr(VI) adsorbent. 2024 The Authors -
Solar radiative heat-driven Sakiadis flow of a dusty nanoliquid with Brownian motion and an exponential space-based heat source: KooKleinstreuerLi (KKL) model
The advancement of heat transportation is a significant phenomenon in nuclear reactors, solar collectors, heat exchangers, and electronic coolers; and it can be accomplished by choosing ananofluid as the functional fluid. Nanofluids haveimproved thermophysical properties, dueto theirgreat progress in engineering and industrial applications. Therefore here, the significance of exponential space-related heat source (ESHS) on radiative heat motivated Sakiadis two-phase flow over a moving plate is analyzed for a particulate nanoliquid (CuOH2O). The impact of the haphazard motion of nanoparticles is analyzed through the KooKleinstreuerLi model. On applying a similarity transformation to the governing equations, a set of ordinary differential equations is obtained and numerically solved. Through the perception of graphs, the behavior of the velocity and temperature constraints for diverse values of effective parameters is decoded. The results showthat the temperature of both phases (dust and fluid) improves with the ESHS aspect. Also, the heat transport rate/friction factor enhances/declines with the concentration of dust particles. 2020 Wiley Periodicals LLC -
Solar pv tree: Shade-free design and cost analysis considering Indian scenario
In this paper, the performance and the cost-effectiveness of a solar PV tree for supplying the energy demand of a flood lighting system at a basketball court in the School of Engineering and Technology, Christ (Deemed to be University) at Bangalore, India, are analyzed. Also, the energy demand of a flood lighting system for year 2017 is estimated (16 kWh/day), and the design of 4 individual trees of 1 kWp each is proposed, which saves around 40 sq.m area of land near to the basketball court. The experimental data was collected from June 1st, 2018 to May 31st, 2019, using a data acquisition system and processed to calculate the monthly cost of energy produced by each tree. In order to reduce the complexity in design and allow it to be shade-free, all the panels of a tree were oriented at the same azimuth angle. Based on technical and economical assessments with respect to rooftop systems, the solar PV tree presented reasonable results and could be a future adoptable technology for high population density areas, as well as for remote applications. Later, the adoptability of the proposed solar PV tree was simulated for 2 kWp, considering the climatic conditions of 2020, for different rural and urban locations of India. From the techno-economic-environmental analysis, it is highlighted that the annual energy yield is more with the solar PV tree model than with a land-mounted SPV system. The cost savings and greenhouse gas (GHG) reduction are also higher with the proposed oak tree-based solar PV tree in urban areas than in rural areas recommending it for practical applications. 2021, Walailak University. All rights reserved. -
Solar PV Tree Designed Smart Irrigation to Survive the Agriculture in Effective Methodology
The global economy benefits significantly from agriculture. However, there are significant issues and difficulties in the irrigation sector as a result of a significant regional imbalance in power supply, water availability, rainfall, and adoption of technology. The most economical approach to supporting agriculture in the modern day is through irrigation powered by renewable energy. Productivity is impacted by environmental issues, defective irrigation systems, and unknowable soil moisture content in agricultural fields. Traditional watering systems might lose up to 50% of the water used due to ineffective irrigation, evaporation, and overwatering. As a result, the proposed study will modify solar tree-based smart irrigation systems that use the most recent sensors for real-Time or old data to influence watering flows and change watering schedules to enhance the system efficiency. One application of a wireless sensor network is proposed for low-cost wireless controlled irrigation and real-Time monitoring of soil water levels using Arduino controllers. Data is gathered for drip irrigation control using wireless acquisition stations powered by renewable energy, which lowers the risk of electrocution and boosts output. 2022 IEEE. -
Solar Mapping of India using Support Vector Machine
Accurate knowledge of global solar radiation (GSR) data is necessary for various solar energy based applications. However, in spite of its importance, the number of solar radiation measuring stations is comparatively rare throughout the world due to financial cost and difficulties in measurement techniques. The objective of this current study is to assess the solar energy potential and to develop solar resource mapping of India without utilizing the direct measurement techniques. GSR is predicted with commonly available meteorological parameters like minimum and maximum temperature as its inputs by using Support Vector Machine (SVM) based solar radiation model. The SVM model is validated with measured data from India Meteorological Department (IMD). This study simplifies the major challenge of preparing GSR data for various solar energy applications in a big country like India. Also the life cycle cost of Solar PV is analyzed in India. The payback period will be around 3 years for an annually solar radiation of range from 3.5 to 6 kWh/m 2 /day. This work eliminates the requirement of costly pyranometer to get GSR data. Solar resource mapping of India is developed without direct measurement technique thus avoids GSR data recording, daily maintenance and subsequently the increasing cost of GSR data collection. 2018 Web Portal IOP. All rights reserved. -
Soil classification using active contour model for efficient texture feature extraction
Precision farming is a systematic approach in agriculture that aims in improving economic and environment status of the farmers. It is achieved by having prior knowledge on soil texture, nutrient, pH and other climatic conditions. Hence this paper proposes a soil classification for crop prediction approach that uses an active contour algorithm for band estimation in Fourier domain for efficient texture feature extraction. This approach initially segments the soil sample and extracts into the color and texture features. The approach proposes a texture feature extraction where the image is initially transformed to Fourier domain of a 2D-discrete Fourier transform. The image in the Fourier domain is classified into high and low-frequency bands. The cut off frequency is decided by final contour of active contour method, where initial circular contour is used for estimating final contours on Fourier coefficients. This leads to the estimation of an irregular-shaped cut off frequency along with the 2D Fourier coefficients, instead of using a circular-shaped cut off frequency. A local binary pattern (LBP) from the high-frequency band image extracts texture feature. The extracted texture and color features are trained using a fully connected network. Active contour-based proposed model was evaluated by metrics F1-score, accuracy, specificity, sensitivity, and precision on soil datasets of Kaggle and IRSID. The accuracy, F1-score, specificity, precision, and sensitivity of proposed approach active contour-based were estimated as 97.89%, 97.87%, 99.46%, 98.11 and 97.94% respectively when evaluated in the Kaggle dataset. The evaluation results of proposed active contour model based soil classification outperform other traditional approaches. 2023, The Author(s), under exclusive licence to Bharati Vidyapeeth's Institute of Computer Applications and Management. -
Software Systems Security Vulnerabilities Management by Exploring the Capabilities of Language Models Using NLP
Security of the software system is a prime focus area for software development teams. This paper explores some data science methods to build a knowledge management system that can assist the software development team to ensure a secure software system is being developed. Various approaches in this context are explored using data of insurance domain-based software development. These approaches will facilitate an easy understanding of the practical challenges associated with actual-world implementation. This paper also discusses the capabilities of language modeling and its role in the knowledge system. The source code is modeled to build a deep software security analysis model. The proposed model can help software engineers build secure software by assessing the software security during software development time. Extensive experiments show that the proposed models can efficiently explore the software language modeling capabilities to classify software systems' security vulnerabilities. 2021 Raghavendra Rao Althar et al. -
Software Quality Prediction by CatBoost: Feed-Forward Neural Network in Software Engineering
Software quality is the key aspect of every software organization. Multiple frameworks and algorithms are essential to ensure quality. However, multiple software failures occur uninvited. There are multiple aspects that skew a softwares efficiency. Now the software quality analysis framework mostly focuses on design flaws and test plans done during development. To overcome this problem of software failure, this research proposes a prediction for software efficiency analysis in software engineering using enhanced feed-forward neural network machine learning classification with CatBoost. This research also evaluates the parameters of efficiency of each software component before implementation. This proposed work also analyses the basic aspects that need to be ensured before the design phase of any software. 2024 Taylor & Francis Group, LLC. -
Software development with UML modelling and software testing techniques
This chapter focuses on software development principles and discusses each principle thoroughly with diagrammatic representation. It also includes the definition of UML (unified modeling language) modelling with an explanation regarding how UML modelling takes place and a detailed example. It also focuses on software testing methods, with each method definition and diagrams well explained. A simple case study situation is taken to discuss the example of UML model. This chapter's main objective is to focus on all key points of software development testing and model design techniques precisely. 2023, IGI Global. All rights reserved. -
Software bug in identification and prediction through software are metrics in object oriented protects :
In the software engineering, quality assurance plays an important role. newlineThe quality assurance as an activity, observes the execution of software project to ensure that the behavior of product is in accordance with the expectations. The testing is associated with quality assurance activities. The testing takes a lot of time and an effort of the tester to test the test newlinecases. Even after enough manual or automatic testing, bugs remain uncovered because of lack of time. So, a need arises to focus on this area to save the time and cost of the organizations. The software developer or newlinetester should be aware about the main reasons of software bugs so that they can focus on the right part of the code at the right time. Need of introducing product, process and project metrics is also very essential for newlinethe identification of major causes of bugs. Predictions will always be best if the history of project is taken into consideration. We can come up with accurate predictors with the help of root causes of the software bugs. Several bug prediction models can use bug indicators as the input of model to predict the number of bugs. newlinePrediction attempts to provide quantitative measures to help the software testers and developers. With more number of bug indicators, a step can be taken towards wider horizon of bug prediction thus enabling higher devotion to improve quality of software products. Therefore, identification of several reasons of software bugs and implementation of effective bug prediction models are needed to widen the scope of bug newlineprediction approaches and to improve the software quality. After estimating the future bugs using prediction models, awareness of bug severity is also required to avoid the expected harms to software products. newlineIntroduction of Artificial Neural Network (ANN) was needed to improve the prediction potential. In this work an attempt has been made to associate different levels and types of inheritance through neural network newlineby establishing a correlation framework with diverse types of bug severitie. -
Soft grafting of DNA over hexagonal copper sulfide for low-power memristor switching
Green electronics, where functional organic/bio-materials that are biocompatible and easily disposable are implemented in electronic devices, have gained profound interest. DNA is the best biomolecule in existence that shows data storage capacity, in virtue of the sequential arrangement of AT and GC base pairs, analogous to the coding of binary numbers in computers. In the present work, a robust, uniform and repeatable room-temperature resistive switching in a Cu/Cu2S/DNA/Au heterojunction is demonstrated. The DNA nanostructures were anchored on the densely packed hexagonal Cu2S structures by simple electrochemical deposition. This heterostructure presents outstanding memristor behavior; the device exhibits resistive switching at a very low threshold voltage of 0.2 V and has a relatively high ON/OFF ratio of more than 102 with a good cycling stability of ?1000 cycles and a negligible amount of variation. The justification for such a switching mechanism is also given on the basis of the energy-band diagram of the Cu2S-DNA interface. Based on the studies herein, the resistive switching is attributed to the reversible doping of DNA by Cu+ ions, leading to intrinsic trap states. Further, the switching is modeled with the help of different transport mechanisms, like Schottky-barrier emission, Poole-Frenkel emission and Fowler-Nordheim tunneling. 2023 The Author(s). -
Soft excess in AGN with relativistic X-ray reflection
The soft X-ray excess, emission below (Formula presented.) 2keV over the X-ray power-law, is a marked spectral component in the X-ray spectra of many Seyfert1 galaxies. We investigate if the observed soft X-ray excess in a sample of Seyfert1s is in accordance with the prediction of the relativistic reflection model by analyzing the XMM-Newton and NuSTAR spectra. The fractional difference in the soft excess (SE) obtained from the blurred reflection emission predicted (from NuSTAR) and the observed (from XMM-Newton) luminosities show that the reflection model underestimates the SE emission in our sample. The results point to alternative models (for example, warm Comptonization) to explain the soft X-ray excess in AGN. 2023 Wiley-VCH GmbH. -
Soft computing techniques for hub sequence analysis /
Bioinformatics, the combination of Biology and Information Technology has become a pioneer industry booming worldwide. One of the grand challenges in biology is to understand organizing principles of bimolecular networks. There seems to be a deliberate effort towards uncovering new laws of biological complexity. One of the most pressing needs in this area is the understanding of protein-protein interaction networks and their complexity. Hub proteins- network elements with high connectivity- literally ??hold the networks together. Though several experimental methods have been developed to identify hub proteins, it is important to supplement procedures for pattern recognition to classify/predict hub protein sequences. This research work aims at the classification and prediction of hub proteins of two model organisms- Homo sapiens and Escherichia coli using different computational approaches of pattern recognition such as Principal Component Analysis (PCA), Artificial Neural Network (ANN) and Linear Discriminant Analysis using (i) Class Dependent Approach (LDACD), (ii) Class Independent Approach (LDACIND), and (iii) Normal Bayes Classification (LDANB). -
Soft Computing Approaches for Maximum Power Point Tracking of Solar PV System
Solar power changes according to irradiance and temperature in a day. A Maximum Power Point Tracking (MPPT) algorithm is actually necessary to obtain the maximum power from the photovoltaic (PV) arrangement. In this paper, in order to optimize power and improve the efficiency of PV module with regulated output voltage, soft computing MPPT techniques, flying squirrel search optimization and artificial bee colony methods are implemented on cascaded double voltage lift boost converter. The PV module is subjected to both with and without constraints to analyze the performance of the DC/DC converter, and the comparative outcomes are evaluated for resistive and different types of battery loads at various temperature conditions in MATLAB/Simulink platform. The optimized power is achieved by using artificial bee colony technique with less ripple in the output waveforms at constant 25 C temperature irrespective of the changes in irradiation with the battery load and this can be used for charging of the battery system. 2023 Praise Worthy Prize S.r.l.-All rights reserved. -
Soft Computing Approach for Student Dropouts in Education System
The education system has increased the number of dropouts in the coming years, decreasing the number of educated people. Education system refers to a group of institutions like ministries of education, local education bodies, teacher training institutes, universities, colleges, schools, and more whose primary purpose is to provide education to all the people, especially young people and children in educational settings. The research aims to improve the student dropout rate in the education system by focusing on students performance and feedback. The students dropout rate can be calculated based on complexity, credits, attendance, and different parameters. This study involves the extensive study that inculcates student dropout with their performance and other parameters with soft computing approaches. There are various soft computing approaches used in the education system. The approaches and techniques used are sequential pattern mining, sentimental analysis, text mining, outlier decision, correlation mining, density estimation, etc. The approaches and techniques will be beneficial to calculating and decreasing the rate of dropout of students in the education system. The research will make a unique contribution to improved education by calculating the dropout rate of students. In particular, we argue that the dropout rate is increasing, so soft computing techniques can be the solution to improvise/reduce the dropout rate. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Sodium alginate/bismuth (III) oxide composites for ?-ray shielding applications
In the present work, we have explored the efficacy of bismuth (III) oxide (Bi2O3) loaded, calcium ion cross-linked solution cast sodium alginate composite films for radioprotective applications. Calcium ion cross-linking increased the water and chemical resistance, which further improved on introduction of Bi2O3 into the composites. The 40 wt% Bi2O3 loaded films showed good heat resistance with the peak degradation temperature reaching as high as 251C. The Bi2O3 loaded composites showed enhanced tensile strength (TS) and Youngs modulus (YM). Compared to high-modulus polymers like epoxy, high-density polyethylene (HDPE) and poly (vinyl chloride) (PVC), these exhibit relatively greater extent of stretching before breaking. The ?-ray attenuation experiments showed that mass attenuation coefficients of the composites at various ?-ray energies increased with filler loading. These composites are effective in shielding ?-rays from radioactive sources like 137Cs, 22Na, 133Ba, and 60Co that are widely employed in several medical and industrial applications. The overall enhancement in thermal, mechanical, and radiation shielding characteristics of the composites may be attributed to the uniform distribution of the fillers in alginate matrix. These nontoxic sodium alginate/Bi2O3 composites can be used as soft and biodegradable radiation shields, which may be processed to wearable forms. 2020 Wiley Periodicals LLC. -
Socioeconomic determinants of COVID-19 in Asian countries: An empirical analysis
The spread of coronavirus disease, 2019, has affected several countries in the world including Asian countries. The occurrences of COVID infections are uneven across countries and the same is determined by socioeconomic situations prevailing in the countries besides the preparedness and management. The paper is an attempt to empirically examine the socioeconomic determinants of the occurrence of COVID in Asian countries considering the data as of June 18, 2020, for 42 Asian countries. A multiple regression analysis in a cross-sectional framework is specified and ordinary least square (OLS) technique with heteroscedasticity corrected robust standard error is employed to obtain regression coefficients. Explanatory variables that are highly collinear have been dropped from the analysis. The findings of the study show a positive significant association of per capita gross national income and net migration with the incidence of total COVID-19 cases and daily new cases. The size of net migration emerged to be a potential factor and positive in determining the total and new cases of COVID. Social capital as measured by voters' turnout ratio (VTR) in order to indicate the people's participation is found to be significant and negative for daily new cases per million population. People's participation has played a very important role in checking the incidence of COVID cases and its spread. In alternate models, countries having high incidence of poverty are also having higher cases of COVID. Though the countries having higher percentage of aged populations are more prone to be affected by the spread of virus, but the sign of the coefficient of this variable for Asian country is not in the expected line. Previous year health expenditure and diabetic prevalence rate are not significant in the analysis. Therefore, people-centric plan and making people more participatory and responsive in adhering to the social distancing norms in public and workplace and adopting preventive measures need to be focused on COVID management strategies. The countries having larger net migration and poverty ratio need to evolve comprehensive and inclusive strategies for testing, tracing, and massive awareness for sanitary practices, social distancing, and following government regulation for management of COVID-19, besides appropriate food security measures and free provision of sanitary kits for vulnerable section. 2020 John Wiley & Sons Ltd -
Sociocultural aspects of the medicalisation of infertility: a comparative reading of two illness narratives
This paper is a comparative reading of variations in the medicalisation of infertility caused by sociocultural aspects, in two illness narratives by patients: Elizabeth Katkins Conceivability (2018), a story of navigating a fertility industry with polycystic ovarian syndrome and antiphospholipid syndrome in America and Rohini Rajagopals Whats a Lemon Squeezer Doing in My Vagina (2021), a discussion from India of a growing awareness of medicalisation in treatment of unexplained infertility. For this purpose, it first charts scholarship on illness narratives and medicalisation, noting a historical association. Following this, it shows how infertility, a physiological symptom of reproductive incapacity or failure to show clinical pregnancy, is generally medicalised. This paper reads the texts as showing hitherto unaddressed sociocultural aspects of infertilitys medicalisation. At the same time, drawing from existing sociological and anthropological scholarship, it shows how a reading of sociocultural aspects in medicalised infertility nuances understanding of its medicalisation. This comparative reading attends to sociocultural values and norms within the texts, including pronatalism, fetal personhood, kinship organisation, purity/pollution, individual reliance, sacred duty and so forth. It draws from scholarship on embodiment, rhetorical strategies and the language of medicine. It also shows how a patients non-medicalised, affective history ofdeep sickness caused by the biographical disruption of infertility is not that of apoor historian. In laying out the particularisation of such sociocultural values and norms across America and India, medicalisations migration from its origins to the margins reveals subjectivised, stratified reproduction in infertility illness narratives. This paper is part of a turn in scholarship away from understanding the medicalisation of infertility as naturalised and decontextualised. Author(s) (or their employer(s)) 2024. -
Socio-economic development of Darjeeling Himalayas: Categorical principal component analysis (CATPCA) and ordinal logistic regression (OLR)
The measurement of regional development plays a crucial role in improving the quality of life of local communities. However, the process of analyzing the regional progress was challenging as regional development was presented as a multidimensional concept. Nonetheless, the study's primary objective was to understand the indicators that genuinely reflect the development process's various dimensions in the northernmost district of West Bengal, Darjeeling Himalayas. Seven dimensions of development, namely psychological well-being, health, education, governance, safety and crime, energy and environment and standard of living were identified for analyzing the socio-economic development of the Darjeeling Himalaya. A questionnaire was framed and circulated in the region for the collection of data. By applying Categorical Principal Component Analysis (CATPCA), the data collected was aggregated into the above mentioned seven dimensions of development and analyzed the relationship between these development indicators through the Ordinal Logistic Regression model (OLR). The results showed that education and governance indicators had a significant impact on psychological wellbeing. Governance was affected by psychological wellbeing, while the standard of living was affected by psychological wellbeing and health indicators in the region. 2021 The Society of Economics and Development, except certain content provided by third parties. -
Socio-economic Development and Value Creation Through Corporate Social Responsibility: A Case Study of Bosch India Foundation
In recent years, it is mandatory for profitable organizations in India to work toward Corporate Social Responsibility (CSR). Many thinkers in the industry have appreciated the move of the Indian Government by mandating profitable businesses to take responsibility for society by sharing certain portions of the profit made by these organizations. This study focuses on various initiatives taken by BOSCH India Foundation (BIF) for socio-economic development and value creation through its CSR activities. The primary data are collected by conducting interviews with the seniorlevel managers working in the CSR department of the Bidadi plant. The data are also collected by visiting the field of action, discussing with various stakeholders and observing their initiatives. The secondary data are collected from published sources and official records of the company. This case study shows that BOSCH India Foundation is focusing on the development of the villages in Bidadi. Their CSR initiatives focus on education, agriculture and livestock development, health and hygiene, environment, women empowerment, youth development and access to potable water. This study analyzes the economic and social impacts it has created in the society. The case provides new insight for researchers and students about the CSR approaches and best practices which can be a model for companies working on CSR projects. 2024 by World Scientific Publishing Co. Pte. Ltd.