bluuebunny/crossref_metadata_2025 huggingface dataset:
Teachers’ Perceptions of Virtual Learning Platforms during Covid-19:a Study at Utas-Ibra, Oman
Authors: Chinnathambi Kodhandaraman , Anandan Latha , Domalaon Donald Villahermosa , Gino Vencelin
Published: April 2022

Online education was introduced as a provisional measure to continue with teaching and learning during the Covid-19 pandemic. At the beginning, teachers and students faced a lot of challenges such as lack of availability of gadgets, lack of technological skills, and technical issues. Nonetheless, they overcame the issues to a great extent in the course of time. Many research studies have been conducted across the globe to investigate the use and efficacy of virtual learning platforms, especially in the educational sector, but only few studies have been conducted in this area at the University of Technology and Applied Sciences (UTAS), Oman. Hence this study was conducted to explore teachers’ perceptions of Virtual Learning Platforms during the Covid-19 pandemic. The study participants (N=56) were the teachers of English Language Centre of the University of Technology and Applied Sciences-Ibra, Oman. The findings of the study have implications for policy redirections. The present study confirmed the previous research findings that virtual learning platforms indeed played a vital role in facilitating online education during the Covid-19 pandemic. Key Words: Virtual learning platforms, education, covid-19, efficacy, perception
Pre-Packaged Insolvency: Exploring an Alternative Framework for Bankruptcy Resolution in India
Authors: Kumar Santosh , Jain Vaishali
Published: April 2022

This article is a review of literature on the need for alternative bankruptcy resolution framework in India. The study explores the context and background to the recent initiation of limited Pre-Packaged Insolvency in India. The article makes a strong case for having a private and pre-negotiated mode of debt resolution along with the existing CIRP framework in India. The article provides a comparative perspective of CIRP and Pre-Pack driven resolution model in India. The research paper also addresses some of the potential challenges and concerns related to initiation of Pre-Pack in India and accordingly discusses the relevant safeguards for the same. Lastly, the study also provide a brief view of Pre-Pack model currently practiced in the USA.
Brexit, International Finance, and Fiscal Capacity in the Long Run
Authors: Pathrose Eugin Prakash , Verma Priyanka
Published: April 2022

The elements that influence, according to this paper, the approach to international finance and financial governance is evolving, with significant employ for the EU's ability to implement its preferences globally. It appears that two related factors are driving this transition. First, European Supervisory Authorities (ESAs) have recently gained popularity in international financial governance due to its unique incentives, priorities, and capacities. Second, as international financial regulation shifts from standard-setting to operational concerns, administrative organizations such as the ESAs have a greater opportunity to exert control. This article examines the consequences of the existence of a social democratic organizational channel by which the EU can engaged with global finance governance using the European Securities and Markets Authority as a research study. The data based on secondary and data collect from the world development indicators. The results analysis run from the smart PLS software and measure the performance of international finance and fiscal capability in the long run. Results indicate that there is inverse but significant relationship between international finance fiscal capability in the long run. The European Securities and Markets Authority has the best track record of any ESA in the world. It also makes some predictions on how the UK's relationship with international finance, also its governance and the ESAs as global organizations, would be affected by the Brexit decision.
The Future of Business Reporting in Accounting and Finance:(LEARNING FROM THE COVID 19 PANDEMICS)
Authors: Pathrose Eugin Prakash
Published: April 2022

This proposed research work aims in filling a gap in the literature by explaining how corporations' lack of understanding of non-financial activities, notably biodiversity, can lead to global economic crises like Covid-19. Work with established companies to improve the quality of their reporting by accounting for non-human components and making it more comprehensive for stakeholders. To back up our argument that nature contains both human and non-human components, we employ Actor Network Theory (ANT) and the Natural Inventory Model. Offering a theoretical framework for the consequences of businesses' non-financial reporting Based on our experiences of the Covid-19 problem and a review of the existing relevant literature on CSR, Covid-19, non-financial reporting, and integrated reports (IR), we developed (IR). Suggesting that businesses implement/adopt the Circular Economy idea as a long-term business model, as well as report on biodiversity and extinction accounting in a more organized and required manner by creating IR to produce value in the close, mid, and longer - term. This is the first research to look at the Covid-19 issue and make suggestions for future reporting. The discoveries will help both academia and society. Advances in information technology are expected to have a significant influence on the future of accounting and reporting. The majority of prior research has focused on technology as the most important factor impacting accounting and reporting in the future.
The Real Effect and Consequence of Regulation Reform in Corporate Finance and Banking
Authors: Pathrose Eugin Prakash
Published: April 2022

In order for a country to grow economically, it needs a stable, efficient, and well-functioning banking system. The province should examine systematically and comprehensively its regulations, and examine how to improve the quality of these regulations, reduce their administrative burden, and remove the confusion they sometimes create. Several studies have pointed to the importance of financial regulation to the performance and safety of banks. The reform of regulatory policies and practices makes businesses more competitive and decreases regulatory costs, boosting efficiency, bringing down prices, stimulating innovation, as well as making economies more adaptable and competitive. We investigated how banking regulations affected financial development in MENA (Middle East-North Africa) countries. We measured bank regulation by proxies like foreign banks, capital levels, and liquidity liabilities. We measured financial development by proxies like private credit, z-scores, and private credit. Similarly, a tool to measure bank supervision includes supervisory power, independence, private monitoring, and moral hazard in addition to the size, activity, and stability of the financial sector. In terms of financial development, regulation of banks made a positive and significant contribution. A major contribution of the study is to demonstrate that reform supervision is also an important component of bank regulation, so that banks can achieve their regulatory objectives and impact financial development as strongly as possible. For MENA countries, this benefit is particularly significant, since an analysis of the data shows that more emphasis is placed on regulation than supervision in financial sector reform.
The Role of Higher Education in UAE: Narrowing the GAP between Employers' Expectations and Students' Perceptions
Authors: Pathrose Eugin Prakash , Verma Priyanka
Published: April 2022

This review targets portraying the view of bookkeeping understudies and assumptions for managers concerning the abilities and information required by accounting graduates and the job of advanced education in a similar cycle. For this, an audit was driven on Twenty-seven associations who use college graduates working in the assembling and monetary areas, tended to by a Managing Director (MD) or Human Resources Director (HRD) and 534 college understudies. They finished a poll that assessed the apparent significance of, and fulfillment with, conventional employability abilities. While the businesses saw an absence of suitable abilities as the greatest hindrance to utilizing graduates, understudies believed just three abilities to be a higher priority than employers: insight in the field, initiative and authority, and field information. Contrasted with understudies, managers respected commitment and readiness to take on additional work as key necessities. As far as fulfillment, understudies were more fulfilled than bosses in nineteen abilities from a sum of 32. This study discovers the role of higher education in thinning the gap between employers' expectations and accounting graduates' soft and technical skills. Alternatively, it also suggests the significance of skills development in the university curriculum to be reinforced to develop skillful human resources in accounting so as to meet the employer expectations.
Woman and Nature: Ecofeminist Sensibilities in Nathaniel Hawthorne’s the Scarlet Letter
Authors: Jahan Mursalin
Published: April 2022

Ecofeminism, a branch of feminism focuses on women’s interactions with the natural world. It is the academic, political and philosophical movement that seeks to develop a connection between nature’s depletion and women’s exploitation. Nathaniel Hawthorne’s The Scarlet Letter, set in the Puritan-patriarchal culture depicts how women were persecuted, tormented, condemned and governed by men in all parts of their existence. Though Hester Prynne, the protagonist of the novel is outraged by the Puritans, she receives God’s affection for her through the gentle impact of nature which inspires her to focus her energy within and seek the inner goodness that urges her to cultivate her inner strength. By applying ecofeminist theory, the present paper attempts to examine the relationship between women and men and women and nature. The current research also assesses nature’s cordial relationship with Hester Prynne and highlights the difference between men and women in their perception of nature.
Face Mask Detection with Automated Door Entry Control Using Convolutional Neural Network
Authors: V Mercy Rajaselvi Beaulah , S Prathima , A.K Savitha , D Shalini
Published: April 2022

COVID-19, the coronavirus infection of 2019, has infected over 172 million people globally and killed over 3.7 million. One of the most prevalent ways for people to protect themselves in public areas is to wear masks. Face mask detection has become a critical computer vision task to control the infection, yet mask detection research is limited. So, real-time detection of the mask is proposed using a deep learning approach with an automated door entry control system. Deep learning plays a major role in Natural Language Processing, object identification, and facial recognition. The proposed system with the face net model incorporates mask detection efficiently and accurately. To detect the presence of a face mask, the trained face mask classifier is applied to the live video stream. The data from the detection phase is passed to an automated door entry control mechanism to control the entry of the people. The experiment is conducted, and the results are obtained. From the results, it is inferred that the system recognizes the presence of a mask and ensures safety through the automated door entry mechanism.
Review of Psychometric Data Analysis for Healthcare Based on Emotional Intelligence
Authors: S Kayalvizhi , K Madhumitha , V Chenchu Lakshmi , S BhavathaRanjanni
Published: April 2022

With the technological advancements in the current world and also due to the COVID-19 pandemic there is high competition among people resulting in locked in syndrome, stress, and various other psychological problems like bipolar disorders, schizophrenia, and severe depression. So, the need for proper psychometric analyzer is tremendously increasing to analyze the emotions of people so that a person’s emotion can be found and necessary actions can be taken according to their health condition. To overcome these issues of people around us, our loved ones and also the issue in the online consultation with psychologists, here is the proposed system. In this system, a person’s emotions are recognized using their video, audio, and text in three different modules separately and an analysis of their emotion are provided. Some of the existing systems helps in identifying the emotion of people in video, audio, and text separately. This system aims at combining the three features separately in a single website and provides analysis for emotion using the best model for each. Identifying a person’s emotions becomes crucial to know about his/her mental state in the pandemic. The main objectives of the proposed system are: (1) To identify the emotion of a person in video, audio, and text using machine learning models. (2) The proposed system makes it easy for the psychologist to identify the patient’s emotions in online consultations.
Modeling and Simulation of Manufacturing Process of Paracetamol
Authors: Husain Taher , Vora Khushi , Meda Ujwal Shreenag , Sarode Manjula , Kallur Vinod
Published: April 2022

Paracetamol is an analgesic and an antipyretic most commonly used for headaches and mild fever. It is very common and almost every individual on this planet has consumed paracetamol at least once in his/her life. So, with that high usage, there is need of a high and efficient production from a paracetamol production plant. In this paper, the manufacturing process of paracetamol is simulated and optimized using the software DWSIM. As paracetamol is one of the most used medicines, therefore its production is also very high. But if production is high then there is a chance that the process is not fully optimized and there is wastage of important chemicals. Optimization will lead to reduction in the wastage, increase the conversion and increase in purity of the compound, and all these factors will lead to driving the cost of production down and in doing so the cost of medicines will also decrease.
Wastewater Treatment Using Anaerobic Fluidized Bed Membrane Bioreactor Coupled with Microbial Fuel Cells for Circular Economy
Authors: N M Shreya , Meda Ujwal Shreenag , Patil Jagadish H , Moses Vinutha , P L Muralidhara
Published: April 2022

Wastewater treatment has been a problem in modern society due to negligence. It has led to the depletion of freshwater resources for human consumption and it is inevitable to search for ways to treat the wastewater effectively and economically. Domestic and industrial wastewaters are not treated well before letting into the freshwater sources. The freshwater gets polluted due to the presence of organic and inorganic substances that are known to be mutagenic, carcinogenic, and harmful to the environment. The conventional wastewater treatment systems are energy-intensive and inefficient. The use of membrane bioreactors is one of the breakthroughs in the field of wastewater treatment, where microorganisms are used to produce energy from the biomass present in the wastewater and utilize it as a substrate for their growth and development. The metabolic cycles of these microbes produce electrons/ions that are utilized in electricity/energy generation respectively. Wastewater usage to produce energy promotes circular economy, but this method alone is not very effective in treating the wastewater. Anaerobic fluidized bed membrane bioreactor with suspended granular activated carbon serves the purpose of a bio sorbent that facilitates the adsorption of low concentration pollutants and reduce the COD levels making it suitable for release into the freshwater resources. Coupling these two methods together seems to be effective and can be scaled up. This review article concentrates on coupling the two mechanisms to promote circular economy.
Interoperability: A Challenge for IoMT
Authors: Yasmeen Gausiya , Javed Nashra , Ahmed Tasneem
Published: April 2022

Internet of Medical Things (IoMT) is the interconnectivity of highly sophisticated medical-grade devices and software applications to work together and provide a new improved version of the healthcare environment in this era. Wearable and standalone devices use sensor technology to exchange medical information from remote areas to health workforces over a wireless network. Apart from being advantageous IoMT faces challenges like safety, cybersecurity and scalability, interoperability, verification, and validation. Interoperability deals with the exchange, interpretation, and usage of data delivered through different computerized gadgets without restrictions. Currently, there are numerous government-certified EHR products each of which has different technical, clinical, and serviceable capabilities. Being heterogeneous it becomes hard to achieve a single standard interoperability format to exchange data. The pivotal aim of this paper is to understand how interoperability plays an important role in healthcare and different ways through which it can be successfully implemented.
Dynamics of Income Diversification, Profitability, and Risk: Analysis of Public and Private Sector Banks in India
Authors: Doshi Archi , Sharma Geeta , Ladha Namrata
Published: April 2022

“Do not put all eggs in one basket.” This risk management principle applies to every other industry whether it be manufacturing or banking. Interest income is believed to be a bank's primary source of income. Banks diversify their operations to generate non-interest income and lower their total risk exposure. Applying panel-data regression, the study analyzes and compares the intensity of diversification of income sources between public and private sector banks in India, using secondary data for Indian financial years 2012-13 to 2020-21. It utilizes RAROA and Z-Score to examine the impact of income diversification on profitability and risk, respectively. It discovered that private banks are more diversified than public banks. With low levels of diversification, public banks had a positive impact on profitability and risk. This is evident from research that banks leverage income diversification as a tool to fight COVID-19 backed slowdown.
Indicators for Exploring the Accountability of Development Cooperation Projects by Supreme Audit Institutions
Authors: Chatterjee Shourjo , Verma Rajit
Published: April 2022

Supreme Audit Institutions (SAIs) are entrusted with providing assurance on the use of funds in implementation of projects by governments. This includes audits of projects and agencies utilizing development cooperation funds. Owing to a research gap in study of accountability of development cooperation projects by SAIs, this study has been undertaken to examine the perception of experts and practitioners in understanding the contribution of SAIs’ audits towards accountability in development cooperation projects. Primary data has been collected by administering a survey questionnaire. Analysis of the responses indicate that audits by SAIs provide accountability in development cooperation projects in terms of the indicators under consideration. The study will enable the different stakeholders in development cooperation including donors and implementing agencies and citizens to place greater reliance on SAI audits as accountability mechanism as part of country Public Financial Management systems.
Evaluating ARITE System Usability for Rendering Hands-on Experience to Engineering Undergraduates
Authors: Kumar Amit , Mantri Archana
Published: April 2022

Hands-on experience through laboratory tasks is essential in engineering education. It allows students to perform experiments designed in their respective courses, which imbibes particular aptitudes and skills. This paper discusses the use of the ARITE system for teaching Embedded System courses to engineering undergraduates. The ARITE system uses Augmented Reality technology to teach underlying concepts of Embedded Systems to students. In addition, a System Usability (SU) test was conducted in which 36 engineering students of different disciplines participated. The SU score for the ARITE system was evaluated as 67.40%, which implies its potential usage in delivering hands-on experience to engineering students.
Machine Learning Based Classification Algorithm for Classification of Dengue (Dengue Fever - DF, Dengue Harmonic Fever - DHF, Serve Dengue - SD)
Authors: Kapoor Rajeev , Ahuja Sachin , Kadyan Virender
Published: April 2022

Dengue is becoming a burden for society worldwide and become a challenge for the world. The main objective of this research paper is to classify dengue at an early stage. The author has adopted a methodology that is divided into five phases namely data collection, transmission of raw data in structural data format, data preprocessing, model building with train and test datasets, and prediction. Further, the proposed prediction model has been trained with the help of 250 data samples from primary sources, namely clinical labs and 1,000 data samples in the form of synthetic datasets adopted from 20 research papers. The proposed prediction model has been tested and validated with the help of comparative study of different machine learning algorithms, namely Decision Tree, Logistical Regression, Support Vector Machine (SVM), Gaussian Naïve Bayes, etc. The proposed model has achieved 97.39% accuracy, 0.98 precision, 0.97 recall, 0.97 F1 Score, 0.02 MS, and 0.14 RMSE.
Domestic Wastewater Treatment Using Neem Leaves and Coconut Husk as Adsorbents
Authors: Paul Sunny , Chavan Farooq , Husain Mujahid
Published: April 2022

From the inception of the Coronavirus pandemic for the more than a year, it has now become exigent that the water supplies and wastewater be treated at its fullest efficiency as their nexus is quite ubiquitous in this domestic society. To design a robust wastewater treatment incurs a hefty cost, so the need of the hour is to resort towards treatment techniques which incurs minimal cost and adsorption techniques are one of them. Adsorption is a process where contaminants or compound in one phase gets attached or condensed to other phase, finally removing them. Adsorption by using activated carbon is a prominent method to remove the contaminants from water and wastewater remarkably, but still many researches shows the same as expensive and therefore, low-cost adsorbents extracted naturally is a best and cheapest alternative to remove the same. Numerous researches showed the potency of such low-cost adsorbents in removing heavy metals, dyes, etc. from the wastewater, but there is no literature available pertinent to the removal of parameters viz. COD, BOD, etc. from the wastewater. The present research aims to study the alteration of functional parameters viz. adsorbent dosages and pH in the removal of COD by comparing its efficiency supplemented with batch adsorption studies on the low-cost adsorbents viz. neem leaves and coconut husk.
Nanotechnology in the Textile Industry: Present and Future
Authors: Ranga Shravan , Meda Ujwal Shreenag , Kiran Samhita
Published: April 2022

The use of nanotechnology in various types of textiles revolutionized the industry. Bulletproof jumpsuits, invisible coatings, advanced fibers, and fabric touchpads have transformed traditional textiles into smart textiles. Artificial muscles, also known as ICPs (inherently conductive polymers), are made from nanomaterials that mimic biological muscles. Fabrics coated with silver nanoparticles are the most effective antibacterial bandages or dressings. New advancements allowed usage of pressure pads which have nanoparticles of gold, nickel, and so on incorporated into it. The piezoelectric capabilities of carbon doped polymers used in iPod controls and fabric switches are preserved. Woven optical fibers are used in textiles for a variety of purposes, including light transmission, sensing, deformation detection, and data transmission. Another approach for the transfer of graphic and multicolored surfaces is light emitting fabrics. Fabrics made with phase change materials act as a thermostat, ensuring that the desired temperature is maintained.
Effects of Convective Boundary Condition and Activation Energy on Chemically Reacting Nanofluid Flow with Radiation
Authors: Lakshmi Devi Gavireddy , H Niranjan
Published: April 2022

The combined impact of activation energy and radiation on the magnetohydrodynamic flow of nanofluid near a stagnation point with the electric field and convective boundary conditions are exposed in this study. By using similarity transformations, the non-linear partial differential equations renewed into non-linear ODEs. The resultant non-linear ODEs were solved numerically by using a shooting scheme. The impact of non-dimensional parameters on temperature, velocity, solute concentration, and nanoparticle volume fraction profiles are discussed graphically. The velocity and solute concentration increased by increasing the activation energy.
An Efficient Two-Layer Framework for Tour Sense Recommendation
Authors: D Deva Hema , Soundrya Sai , Kumaran Bharath , V Harini
Published: April 2022

The paper shows a cutting edge prototype system, which can recommend most comprehensive travel plans that include brand new, diverse latest interest factors (POIs). It systematically gathers and analyzes data on thousands of cutting-edge tourism destinations and geographical nodes. Tour feel is a recommendation framework which examines the preference information modern day diverse tourists based totally on the transport records collected from various towns. Humans can get properly-in shape path plans, which consist of a sequence brand new points cutting-edge interest (POIs) primarily based on vacationers' constraints and goals, way to the advancement ultra-modern excursion recommendation. Multiple scenic spots and entrances are common in big-scale POIs, which are known as brilliant-POIs in this article. Maximum contemporary excursion advice algorithms, alternatively, forget the big expertise determined inside super POIs. A layer machine, which takes into account the ultra-modern route architecture (outer model) and panoramic routes within outstanding POIs (internal model). A full-on-integration-based Embedded Keep VND algorithm is used to merge templates. A greedy randomized adjustable path advent system (grasp) for local improvements in the internal version of the outer version and variable neighborhood descent (VND). The first rate-POI is considered "meta node" in the development of trendy outer routes. Dijkstra Algorithm with Pruning dynamically reviews the most satisfying path within the exquisite POI in the internal model to conform to the outer direction. The obtained end results provide the traveller with the ultimate quality route and the focus point chosen by the users.
Correlation of Distance Based on Topological Indices and the Physio Chemical Properties of Alkanes
Authors: M Puruchothamanayaki , F Simon raj
Published: April 2022

In graph theory, topological indices play a vital role for finding the degree and distance based topological indices. Here we are using the distance based topological indices. In this article, we are calculating the mostar index value for the structural isomers of 44 alkanes. After finding the mostar value, we are correlating the mostar value and the physicochemical properties (boiling point (BP), molar volumes (MV) at 20 degrees c, heats of vaporisation (HV) at 25 degrees c, surface tension(ST) at 20 degrees c, and melting point (MP) of 44 alkanes. Suppose the correlated value is between 0.8 and 0.9. Then the correlation is nothing but a good correlation. So, in this case, finally we conclude that in what level the one of the distance based topological index mostar is predicted that the physico chemical properties of the structural isomers of the 44 alkanes.
Recent Progress on the Synthesis and Applications of Cu@CD
Authors: Sudan Shubam , Khajuria Ajay , Kaushal Jyotsna , Kapoor Mohit
Published: April 2022

Metal doped carbon dots (CDs) have been extensively studied due to their tunable and strong fluorescence emission properties, which make them applicable for sensing, organic catalysis, optronics, and biomedicine. This has attracted the attention of many researchers to develop transition metal-doped CDs. In this article, we have discussed various syntheses and applications of copper doped CDs (Cu@CDs). We have mainly focused on copper because of its various advantages, such as low cost, low toxicity, natural abundance, and ability to show 0-III oxidation states which give them access to show both one and two-electron processes. Majorly, we have briefed on the recent progress in the synthesis, functionalization, and applications of Cu@CDs using chemical reduction, hydrothermal, solvothermal, thermolysis, and green synthesis from various chemical and natural carbon pre-cursors. Afterward, we have discussed their applications in analyte detection and sensing, organic catalysis, anti-microbial activity, bio-imaging, and cancer therapy.
Impact of COVID Vaccination: A Machine Learning Approach
Authors: Gupta Ekata , Goyal Mukta , Srivastava Abhishek , Pathak Anchal
Published: April 2022

The speed with which the COVID-19 pandemic has spread is astounding, but the global response is based on lessons learned from earlier sickness outbreaks in recent years. In a human test immunization study, solid volunteers are given a test antibody and afterward intentionally presented to the life from making the sickness check whether the antibody works or not. Nonetheless, there are significant moral contemplations that should be tended to especially for another infection like COVID-19, which perhaps not yet completely comprehend as yet it tends to figure out how to treat. It could be hard for the clinical local area and expected volunteers to appropriately appraise the possible dangers of taking an interest in a COVID-19 human test study. The investigation is completed utilizing managed AI calculations where it has been attempted to foresee the yield with greatest exactness.
Detection and Classification of Skin Disease Using Modified Mobilenet Architecture
Authors: Anand Vatsala , Gupta Sheifali , Koundal Deepika
Published: April 2022

Skin is an outer covering of body that acts as protection layer from the UV rays of sun. Nowadays, skin disease cases are increasing, so there is a need of a system that can detect skin disease at an early stage. Deep learning is the most efficient, supervised, time- and cost-effective method that has attained outstanding performance in the medical field. These algorithms are fast, and has shown their success and adaptability in different sectors. In this paper, a pre-trained Mobilenet architecture is modified by removing the last five layers and adding one average pooling layer, one dropout layer and one dense layer. The modified Mobilenet architecture is simulated on HAM10000 skin disease dermoscopy dataset. Different transformation techniques have been applied for data augmentation to solve the problem of data imbalance. The model has attained an accuracy of 90%, followed by precision of 86.14%.
Adsorptive Sequestration of Toxic Congo Red Dye from Aqueous Solution Using Fe3O4/Sugarcane Bagasse Biochar Nanocomposite
Authors: Dharmendra Godaba , Sahoo Jitendra Kumar , Hota Amrutashree , Sahoo Shraban Kumar
Published: April 2022

In the current scenario, removal of toxic dyes from dye contaminated water has become a major challenging task to world researchers because disposal of untreated dye effluents into water bodies have adverse effect towards the ecosystem. Keeping this in mind, the present study aims to utilize the sugarcane bagasse biochar (SBB) and its composite with iron oxide nanoparticle (Fe3O4/SBB) to estimate for the decontamination their batch scale potential of Congo red (CR) dye from aqueous solution. The synthesized adsorbent were characterized by FT-IR, XRD, FE-SEM, TEM, VSM, EDX, and BET surface area analysis. The effect of adsorbent dosages (50-130 mg), initial CR concentration (10-100 mg/L), pH (3-11), and contact time (5-240 min) were evaluated CR removal on Fe3O4/SBB at room temperature. The adsorption data well fit with Langmuir isotherm (R2 = 0.99) and pseudo second order kinetics (R2 = 0.99). The maximum adsorption capacity was found to be 74.07 mg/g.
Synthesis of CuI/Sn-ZnO Based p-n Heterojunction Photoanode for Photoelectrochemical Water Splitting
Authors: Banerjee Sanchari , Thangavel Rajalingam
Published: April 2022

Harvesting energy from the sun is contemplated to be one of the notable choices to meet the ever-increasing energy demands of the current progressive society. Photoelectrochemical splitting of water (PEC-WS) into H2 and O2 turned out to be a constructive strategy to overcome the prevailing energy crunch. In this present work, ZnO is doped with different concentrations of Sn and coupled with CuI to construct a p-n heterostructure. Compared to bare ZnO, CuI/5% Sn-ZnO manifested better absorbance in the visible region, enhanced photocurrent density (1.08 mA/cm2), more negative flat band potential, high charge carrier density and least semi-circular arc radius in Nyquist plot. Hence, the present work delineates p-n heterostructure and their nano-engineering opens a potential route for fabricating light-harvesting photoelectrodes to be used for an improved PEC-WS applications.
Volumetric and Acoustic Studies of Interactions between L-Phenylalanine and 1-Hexyl-3-Methylimidazolium Bromide in Aqueous Solution
Authors: Sharma Ravinder , Kumar Harsh
Published: April 2022

Experimental density (ρ) and ultrasonic velocity (c) for phenylglycine in ( 0.01, 0.03, 0.05 and 0.05) mol.kg−1 aqueous solutions of 1-hexyl-3-methylimidazolium bromide at T = (313.15 and 318.15) K. Collected values for density and ultrasonic velocity were used to compute the apparent molar volumes (V

f
), the apparent molar volumes at infinite dilution (), partial molar isentropic compression (K

f

,s
) and partial molar isentropic compression at infinite dilution (). Also recorded data of these mixtures were utilized to calculate pair and triplet interaction coefficients. Such thermodynamic characteristics can be used to investigate the solvation behaviour, structure formation, and many sorts of interactions in (phenylglycine + water + 1-hexyl-3-methylimidazolium bromide) ternary solutions.
Classification of Power Quality Disturbances in Emerging Power System Using Discrete Wavelet Transform and K-Nearest Neighbor
Authors: Kankale Ravishankar Shaligram , Paraskar Sudhir Ramdas , Jadhao Saurabh Sureshrao
Published: April 2022

This paper presents a wavelet and machine learning-based approach for the classification of power quality disturbances (PQDs) in emerging power systems. Renewable energy resources-based distributed generation (DG) is rapidly being used in the emerging power system to address the ever-increasing energy demand. PQDs are thought to be caused by the power electronic converters used in DG systems, DG operating conditions, and other common factors such as faults, switching activities, and non-linear loads. These PQDs must be detected and classified since they can create a variety of difficulties in end-user equipment. The proposed algorithm comprises the simulation of the emerging power system with a solar PV system, creating PQDs cases such as voltage sag, voltage swell, and voltage interruptions, capturing voltage signals which will be further processed using a discrete wavelet transform for feature extraction. The features extracted from DWT analysis are further used to develop the machine learning-based classifier for classification of PQDs. The proposed algorithm has been tested on a variety of PQDs. The simulation result shows that the proposed algorithm is efficient and it outperforms in the classification of PQDs.
Study of Onboard Hydrogen-Rich Gas Generation for Gasoline Engine by Gasoline Steam Reforming with Exhaust Gas Energy Recovery
Authors: Long Hoang Dinh
Published: April 2022

This study was to investigate the potential for hydrogen-rich gas generation, the clean fuel, for gasoline engines by onboard gasoline steam reforming with exhaust gas energy recovery. The study was conducted on a motorcycle gasoline engine of 100 cm3 swept volume in a laboratory combined with modeling. The modeling study was to determine the optimal feedstock conditions for high generated hydrogen yield while the experiment was to validate and confirm the solution. The study accounted for all the aspects of major chemical reactions and heat and mass transfer phenomena in the reformer. A computer simulation code has been developed for the study. The results showed that by taking advantage of exhaust energy, the optimal operating conditions of the reformer for high hydrogen yield were under engine full load with inlet fuel flowrate of 110 g/h and mass water to fuel ratio of 3.5:1. Under these conditions, gasoline conversion of up to 80% and H2 yield of 30.8 g/h was achieved.
A Study of Consumer Behaviour Towards Hair Care Product (Shampoo) in Nagpur
Authors: Shete Bhakti Ramesh , Phule Prashant Namdev
Published: April 2022

The purpose of this study is to understand consumer behaviour towards the purchase of shampoo in Nagpur. Researchers are studying the factors that influence the behaviour of consumers towards shampoo to find out the range of shampoo brand awareness among consumers and also to study the regularity of consumption of a particular brand. All the variables studied were significantly related to demographic factors, consistency, and consumer behaviour at the time of purchase. Researchers have used tools like chi-square to determine the factors affecting consumer behaviour towards the purchase of shampoo. The chi-square test shows that there is a significant association between age and consistency, price and consistency, and type of ingredient and consistency in the purchase of shampoo. The analysis of the hypotheses proved that there is no significant association between age, price, type of ingredients, and consistency. These factors do not influence consumer behaviour at the time of purchase.
Temperature Dependent Morphological and Electro-Optical Characteristics of Dye Doped Cholesteric Liquid Crystal
Authors: Gahrotra Ridhima , Sharma Vandna , Dogra Ankit Rai , Malik Praveen , Kumar Pankaj
Published: April 2022

Cholesteric liquid crystals (CLCs) have gain remarkable attention due to its property of stabilizing the planar (P) and focal conic (FC) states. This paper presents the temperature dependent behavior of cholesteric liquid crystal (CLC) mixed with appropriate amount of dye. The pitch of sample corresponds to visible region (~1 µm) was adjusted by adding appropriate concentration of chiral dopant. The phase transition and morphological behavior was recorded using polarized optical microscope (POM) from planar state to isotropic state by heating the sample using temperature-controller. Experimental results indicated that increase in temperature impacts the morphology of CLC and strongly affects its electro-optical (E-O) properties. Further, POM studies showed that at room temperature dye doped CLC cell has initial transparent state (planar texture) however, when driving voltage was high (~27V) with lower frequency of 1 kHz, P state switched to FC state. On further increasing the temperature, minor distortion was observed in P state in comparison to P state of dye doped CLC cell at room temperature, however, at higher (~ 45˚C) temperature, low driving voltage was required to achieve the stable FC state. Further, FC state was switched to stable P state on applying high frequency (50 kHz) voltage. Afterward, above 45˚C temperature, the textures showed the sustained FC state of dye doped CLC cell with no switching to P state on applying high frequency (50 kHz) voltage. Thus, temperature dependent dye doped CLC cell showed the bi-stability feature upto 45˚C temperature, however, above this temperature showed the fixed FC state.
Synthesis of Silicon Di Oxide Nano-Particles By Sol-Gel Method for Applications in Geopolymer Composites
Authors: K C Sachin , . Radhakrishna , Meda Ujwal Shreenag
Published: April 2022

The advent of nanotechnology has revolutionized the major sectors of science and technology. However, synthesis methodology plays a prime role in deciding the size, shape, and purity of nanoparticles. The sol-gel method of synthesis can control the size and morphology of nanoparticles. It is one of the simplest ways to produce nanoparticles in pure form from the bottom-up approach. In this study, silica nanoparticles were produced through the sol-gel method. Sodium silicate was used as precursor material, with ethanol as solvent. CTAB and Ammonia were used as catalyst and reducing agents respectively. The synthesis process was followed by 4 hours of calcination. The obtained nanoparticles were subjected to FESEM, EDAX, XRD, and PSD analysis. From the results, it is observed that the synthesized nanoparticles had an average diameter of 26nm.
Use of Alexnet Architecture in the Detection of Bone Marrow White Blood Cancer Cells
Authors: Saro Sujithraa Gladys , S Karthigaiveni , S Janani , G Hymlin Rose S
Published: April 2022

The cancer-affected area in white blood cell pictures is studied in this paper. AlexNet architecture is used to classify different types of white blood cells. This model, which was trained on cell pictures, first preprocesses the photos before extracting the best feature. The feature is extracted using the convolutional layer, Relu layer, and max pooling layer. For categorization of Eosinophils, Lymphocytes, Monocytes, and Neutrophils, the extracted features are input into a softmax and a completely linked layer. The various phases of image processing are used to improve the quality and accuracy of blood cancer detection. The accuracy of the blood sample image is determined by the affected area.
An Efficient AES Algorithm for Cryptography Using VLSI
Authors: T Ramya , G Ramya , Raju Karthik , J Ravi , Verma Deepak
Published: April 2022

In today's data exchange framework, information security is the most important consideration. Encryption is a key component of Information security and is used extensively. Encryption techniques are used by all sorts of organisations to protect sensitive data. An technique known as Data Encryption Standard (DES), which uses the same key for both encryption and decryption at the same time, was the first to be employed. That algorithm's key drawback is that it is readily hacked and vulnerable to attacks. Compared to DES and Triple DES, the calculations require enormous memory space and cannot be performed on the hardware stage. There are numerous ways in which AES, the Advanced Encryption Standard algorithm, has supplanted DES. An effective cryptographic method, AES uses multiple key lengths and surpassed DES when compared to other algorithms, such as SHA-1. It is possible to implement equipment stage circumstances inferable from the reconfigurability, cheap cost, and publicizing space with the use of field programmable entryway clusters (FPGAs). To scramble and decode complex data, the RIJNDAEL algorithmic guideline uses a square figure. It also supports cryptographic keys with lengths of 28,192 and 256 bits. The round keys, which are used throughout specific emphases of encryption, are developed in simultaneously with the Encryption strategy, which is a remarkable normal for the proposed pipelined design. Dual-stage architecture is the key to the expansion. It is possible to run at higher clock frequencies with this method, resulting in increased throughput and lower power use.
Analysis of Employability Skills Among Rural Graduates
Authors: K L Sagayaraj , Ashokan Nisha
Published: April 2022

The purpose of education is to bring out the good qualities that are hidden among students. Education enlightens and creates new job avenues for the graduates to hone their employability skills. Employers look for graduates who are acquainted with expected employability skills fit for the job market. Academicians and academic institutes have a vital role in imparting knowledge and shaping the future of graduates. Employability skill creates new hopes and promises to the graduates to secure a promised job. Employability skill is well described as the attributes, knowledge, and skills possessed by graduates during the academic pursuit. As employability skill is becoming more important for the graduates to get good placement, it is the need of the hour to explore new ways of imparting employability skill among the graduates. This article aims at exploring the existing literature on employability skills among graduates. The purpose of this study is to analyze the various dimensions, categories, and frameworks of employability skills among graduate students. This article identifies the gap that is existing between academic institutions and employers. This paper focuses also on the important skills that are expected by employers in the 21st century.
Power Quality and Low Voltage Ride Through Capability Enhancement in Wind Energy System Using Unified Power Quality Conditioner (UPQC)
Authors: Kabat Subash Ranjan , Panigrahi Chinmoy Kumar
Published: April 2022

The various approaches used to improve the Low Voltage Ride Through (LVRT) capabilities of DFIG-based wind turbine systems are investigated in this study (WT). The Type-III WT machine, which is primarily based on DFIG, is connected to the grid without a digital power interface, resulting in unmanageable terminal voltage or reactive electricity output. As a consequence, novel LVRT approaches based on the deployment of additional active interface technologies were given in this work. The problem of low voltage faults is now being addressed using a variety of approaches. By analyzing LVRT approaches for DFIG-based WECS, this research attempts to discover such working ways by bridging the gap in terms of overall adaptive performance, operative complexity of controllers, and cost-effectiveness. This study suggests ways to improve LVRT's ability to rely on the relationship arrangement in three major areas based on their grid integrations. The wind turbine system is connected to a DVR, STATCOM, and UPQC in this study for active and reactive power regulation throughout the fault detection procedure. Using UPQC with SRF theory offers improved reaction during faults to increase active power and maximum compensation in reactive power with synchronous reference frame and without synchronous reference frame operation presented in this paper.
Radial Basis Function Artificial Neural Network Optimized Stability Analysis in Modified Mathematical Modeled Type-III Wind Turbine System Using Bode Plot and Nyquist Plot
Authors: Ganthia Bibhu Prasad , Barik Subrat Kumar , Nayak Byamakesh
Published: April 2022

Stability is the major factor that should be maintained in every power system. To predict and to optimize the nonlinear parameters this research provides a control system transient analysis using Bode plot and Nyquist plot to regulate the stability in wind power generation. The rotor speed should be balanced with respect to the generation of generator power for viable wind power generation. This study introduces a sliding mode controller for controlling wind speed and preserving system stability, and it may be improved using an Artificial Neural Network based Radial Basis Function Neural Network to eliminate nonlinearities induced by changing wind speed. The tip speed ratio approach is utilized in this study to harvest the most power from wind energy. To optimize this TSR method, a PI-RBFN tuned sliding mode controller was utilized to get maximum power while minimizing active power losses. This proposed approach may be used to address nonlinearities in the pitch angle caused by changing wind speed. As a result, the resilience of the redesigned Type-III wind turbine system is investigated using MATLAB simulink in this study. The simulation results are compared to the current DFIG-based modified Type-III wind turbine method.