bluuebunny/crossref_metadata_2025 huggingface dataset:
Impact of Coronavirus on Consumer Behavior
Authors: Raza MD DANISH , Nikhat Reshma
Published: April 2022

India being worst hit during the second wave of coronavirus left a devastating effect on lives and economy. India is facing the greatest crisis since its independence and people are feeling unsecured because of this deadly virus. Lockdown and social distancing have changed not only the consumer buying habits but also the shopping preferences. As coronavirus progressed the consumer optimism declined in India. Consumers are worried about personal and family safety. A majority of people are trying to do their work from home and stepping out only to buy the essential goods. This crisis has affected brand, category preferences, buying behavior, and spends. As purchase decision people are spending higher on their health and hygiene products and preferring home deliveries rather than visiting stores. People have adopted low touch activities which has increased digital payments and online transaction. This paper attempts to examine the impact of coronavirus on consumer behavior.
Extractive Text Summarization Using LSTM-Based Encoder-Decoder Classification
Authors: Thakare Abhijeet Ramesh , Voditel Preeti
Published: April 2022

Nowadays, text summarization is one of the important areas to be focused on. As the World Wide Web is growing, a huge amount of text articles (especially blogs, scientific articles) are also generated on the internet. Automatic text summarization is one of the important techniques to shorten the original text in such a way that shorten or summarized text covers incisive and meaningful sentences of original huge text. Extractive summarization extracts important sentences from original documents and then aggregates all these sentences to generate the summary. We have proposed a novel LSTM based encoder-decoder, which plays a vital role in the extractive text summarization process. CNN news article dataset is utilized for training our model. Our model is evaluated on standard metrics like Gold Standard, Recall Oriented Understudy for Gisting Evaluation (ROUGHE)-1, and ROUGHE-2. After evaluation, our model achieved an average F1-Score of 0.8353. Our model also outperformed other models available in the literature.
Effect of Substrate Temperature on Porosity and Gas Sensing Properties of SnO2-B: Doped Polypyrrole Thin Films
Authors: Hagaragi Anita R , Patil Nirdosh , Reddy Ambresh
Published: April 2022

Porous SnO2-B: doped polypyrrole thin films were synthesized by the dissolving 0.15M of stannous chloride (SnCl4.5H2O) (10%, 20%, 30%, 40%, and 50%) in 25ml of ethanol and adding 4% of Boric acid (H3BO3) and polypyrrole (1:1) using chemical spray pyrolysis technique. Studies on effect of substrate temperature on porosity of the deposited films were at four different temperatures ranging 200⁰C to 280⁰C. The H2S gas was used to study the gas sensing behavior of deposited films and all films were characterized by using IR, XRD, SEM, UV-Vis spectrometry, and current-voltage measurement.
Miniaturization of Microstrip Antenna Using Techniques of Meandering, Loading, and Bending Slots
Authors: Awal Iddrisu , Rai Laxmisha , Wang Zhuopeng , Liu Fasheng
Published: April 2022

One of the existing challenges while realizing miniaturization of the antenna is ensuring that the performance of the antenna without any negative effect has become the main focus of many researchers and pose challenges towards microstrip antenna research. In this paper, we focus on the study of miniaturization of microstrip antennas by designing miniaturized antennas, and carry out modeling and simulation. On basis of existing theory, the proposed method introduces the miniaturization technology of three mainstream microstrip antennas, namely meandering, loading, and bending slots. The electromagnetic simulation software HFSS is used to analyze the influence of the parameters of the three technologies on the antenna performance, and respectively propose a miniaturization scheme of the microstrip antenna.
Accuracy Improvement in Disease Identification of Mango Leaf Using CNN Algorithm Compared with Fuzzy Algorithm
Authors: M. Sivaram Chowdary , R Puviarasi
Published: April 2022

Aim: The main aim of this work is to measure the accuracy in the identification of mango leaf diseases using Convolutional Neural Networks (CNN) compared with Fuzzy Logic. Materials and methods: The data set contains 10 images collected from the seed buzz website and these images are used for training and testing the predictive model in MATLAB. Statistical analysis is done using SPSS software. In the SPSS tool, the measured accuracy of CNN is compared with the Fuzzy model accuracy. Result: The proposed system using CNN achieved high accuracy of 95.2%, whereas the fuzzy mean algorithm gives an accuracy of 93.5 with the significance value 0.038 for accuracy and 0.073 for sensitivity. Conclusion: The outcome of the study confirms that the CNN-based model provides better results in enhancing the accuracy of disease identification in mango leaves.
Work and Family Conflict Among Work from Home Employees during Covid-19 Pandemic
Authors: Jonathan W Cyril Allen , Jayakumar K N
Published: April 2022

United Nation’s Sustainable Development Goal No.3: Good Health and Wellbeing, ensures healthy lives through the promotion of well-being for all ages. Currently, the world is facing a global health crisis unlike any other due to the Covid-19 pandemic. The Pandemic is escalating human suffering, destabilizing the global economy, and upending the lives of billions of people around the globe. Due to pandemic, work from home is the only option for most of the employees in the Education and IT sectors. Due to this unexpected change in their work and family life, conflicts arise and they struggle to balance their work and family life. In this context, this study has attempted to examine the experience of Work-Family Conflict and the Family-Work Conflict among employees who work from home during the COVID-19 pandemic. An incidental sampling technique was utilized to collect the data using Google Form. Participants (N=223) responded to The Work and Family Conflict Scale (11 items), Wallach’s Organizational Culture Index (15 items), Multi-Dimensional Scale of Perceived Social Support (12 items), scales. Results revealed that the work to family conflict factor had a negative relationship with social support and organizational culture as well as family to work conflict also had a negative association with the social support and organizational culture. organizational culture was positively related to social support. Regression analysis revealed that 28% of the variance in organizational culture and social support is influenced by work and family conflict. 31% of the demographic variables was influenced by work and family conflict.
IoT Powered Smart Hydroponic System for Autonomous Irrigation and Crop Monitoring
Authors: Bhargava Yash Vardhan , Chittoor Prithvi Krishna , C Bharatiraja
Published: April 2022

Agriculture has proven to be an integral part of human history and evolution. Traditionally, farming has been a tiresome task. It demands excessive physical effort and knowledge of geographical factors. Apart from this, the yield from the conventional method is prone to dangers such as insect attacks, rotting, and exposure to unfavorable environmental conditions. Hydroponic and IoT can prove to be an effective solution to the above shortcomings. In this article, a smart, self-monitoring, and regulatory system have been proposed. It is devised to monitor and regulate the plant growth parameters to the levels optimum for plant growth. This paper proposes a smart IoT based automatic monitoring and regulating system for spinach hydroponics. Various sensors such as EC-3190 and DHT11 are separately used to monitor parameters such as water levels, temperature, humidity, and light intensity. Wi-Fi technology has been used as a communication channel that connects the user with the hydroponic system remotely.
Effective Coloring in Fuzzy Graphs
Authors: Prabhavathi K , Jayaprakash P , Arockiaranjithkumar M
Published: April 2022

Coloring is the one of the important research topic in graph theory. An effective coloring is an ideal research topic in graph theory. In this paper, the coloring in fuzzy graph are investigated. In a fuzzy graph (FG), an effective coloring function is a mapping such that it is an effective edge in. In this research, the idea of an effective coloring is presented. Further investigate on effective coloring in operation of FG, like join, strong product, semi product, composition, etc.
Magnetic Properties of Undoped and Bi-Doped LaMnO3
Authors: V Devan Chinnu , Deb Biswapriya , Varma Manoj Raama
Published: April 2022

Non-stoichiometric LaMnO3 exhibit attractive magnetic properties and finds various applications. The present work is focused on the magnetic properties of the undoped and Bi-doped LaMnO3. The excess content of oxygen generation during the synthesis leads to the self-doping effect in the sample. The material was synthesized through the conventional solid-state method, and XRD confirms the orthorhombic phase with space group pnma. It shows ferromagnetic (FM) order, and TC decreases with Bi content. The positive C-W temperature further confirms FM. The bifurcation in ZFC-FC introduces the glassy behavior of the material. The excess oxygen in LaMnO3 generates Mn4+ ions and that leads to the reason for FM.
Deep Transfer-Based Skin Carcinoma Detection
Authors: C K Raghavendra , K C Srikantaiah
Published: April 2022

With the emergence of several pollutants, cosmetics, and chemicals into our day-to-day lives, skin cancer is becoming a common disease. Machine learning and image processing is used for identification of type of skin cancer. Several algorithms have been proposed to detect skin cancer, but most of the inputs are fed manually. Manual testing for skin cancer is difficult and strong similarities between different skin types can lead to false detection of lesions classes. To overcome this problem, we propose an algorithm which requires minimal intervention of doctors when provided with an input affected skin image. Images of the affected area are captured with the help of derma scope and fed to the model. The model initially checks whether the image contains a skin tissue that has cancer or not and if it has cancer then classify into which class of cancer it is, whether it is melanoma, nevus, or seborrheic keratosis. Skin cancer segmentation, along with the same evaluation criteria and the results, also showed that the individual accuracy of each class of skin cancer is computed in efficient manner. The models iteratively learn from its past experience and make the model more enhancing. By 2021, there will be 6.3 billion smartphone subscriptions, which might enable low-cost universal access to skin cancer diagnostic services.
Carbon Dioxide Neutralization Across the Global Supply Chain
Authors: Oommen Koshy P , Kurian Sijin , Joy Dr Justin
Published: April 2022

The increased impacts of climatic change and global warming has led many organizations to adopt green initiatives in several areas of their business processes. Many multinational companies are moving towards reduction of carbon emission across its various operations. Carbon neutrality is the process where steps are taken to achieve net zero carbon dioxide emissions. This article proposes measures to achieve carbon neutrality across the supply chain globally. As part of its sustainability initiative, organizations have decided to reduce carbon consumption across their plants. This calls for estimation of carbon dioxide emissions and reducing the carbon footprint in the entire supply chain process. It also involves gauging greenhouse CO2 emissions during the transportation process for all TMC regions and transportation models used by various companies. The main calculations include total CO2 emissions, CO2 emissions per ton of goods transported, CO2 emissions per transport Km. These calculations are done based on factors such as full truck load, less truck load, sea mode of transportation, and air mode of transportation. An analysis is performed on the resulting calculation figures for different modes of transportation such as road, air, and sea. The analysis shows that there is an increase in overall CO2 for air mode of transportation. The least increase in overall Co2 is sea mode of transportation. Through this analysis, it helps the company to take better decisions regarding the mode of transportation that they need to adopt to achieve carbon neutrality.
Hybrid Gradient Strategies in Event Focused Web Crawling
Authors: Rajiv S , Navaneethan C
Published: April 2022

Crawling is defined as the automated and systematic collection of useful web pages with an interconnecting link structure. Live web crawling that is dependent on human, expert-nominated seed URIs is employed for the general construction of event collections. In the focused web crawling technique, the crawler is guided by reference content that pertains to a particular event. With this technique, a focused crawler will attempt to predict if a target URL is directed towards a relevant web page prior to retrieving it. However, it can get trapped within a limited web community and overlook relevant web pages outside its track. For web crawling optimization as well as for the selection of more relevant web pages for retrieval by the crawler, a metaheuristic algorithm is employed. A global searching algorithm’s modification can address the problems. The utilization of basic heuristic algorithms and prohibition techniques forms the basis of the Tabu Search (TS). Swarm intelligence is used by the Particle Swarm Optimization (PSO) to identify an optimization problem’s solution. This is done by a generation of better candidate feature subsets as per a given ﬁtness criteria and rapid convergence towards a global optimum within a set number of iterations. Hence, the proposed gradient-based algorithm will present a more rapid convergence for the PSO than the other variants. A proposal for a hybrid Stochastic Gradient Descent-Particle Swarm Optimization has also been presented in this work.
Comparative Study on Thermal Analysis of Extended Surface Using ANSYS Simulation
Authors: Kumar Hrishikesh Rajesh , Antony M T Arun , S Warrier Shyam , Prabu S. Senthur
Published: April 2022

Extended surface are heat exchangers generally made on the external circumference of an object that are mainly used to enhance the heat transfer rates through a combination of conduction and convection mode of heat transfer. In general, extended surface are made up of the materials whose thermal conductivity is maximum to facilitate more amount of heat transfer to or from the environment and also available in different profiles with respect to the applications of the components. Among the different types, the most commonly used are longitudinal type of fins, i.e. when the direction of flow of the fluid is parallel to the axis. In this research work, an attempt has been made to compare three different profiles like rectangular, trapezoidal, and concave parabolic fins using ANSYS simulation software. Thermal analysis using ANSYS simulation is one of the important techniques to analysis the efficiency of the fin with different profiles. The model of the fin profiles is made by fusion 360 and the comparative study on thermal analysis is carried by employing ANSYS simulation. From this research output, the trapezoidal of the extended surface has better results than the conventional rectangular as well as profile concave parabolic in various thermal properties, and hence it is great replacement of in near future.
Hatching Success and Egg Size of Anisops Sardeus Herrich-Schaeffer (Heteroptera: Notonectidae): A Seasonal Study
Authors: Chanu Chongtham Memtombi
Published: April 2022

Variations in hatching success rate and sizes of eggs of A. sardeus were assessed in different seasons. Percent of egg hatched during the monsoon season (28.95±0.31oC) was higher, about 45.20, 29.26, 19.89% than those in the winter (26.97±2.40oC), post-monsoon (25.92±1.06oC), and pre-monsoon (20.08±1.68oC) seasons, respectively. On contrary, the length and width of the eggs during the monsoon season (1.56±0.08 and 0.58±0.06 mm, respectively) was smaller than those in the winter (1.81±0.06 and 0.79±0.05 mm, respectively), post-monsoon (1.62±0.04 and 0.64±0.05 mm, respectively) and pre-monsoon (1.74±0.10 and 0.70±0.04 mm, respectively) seasons. The variation in the percent of egg hatched and egg sizes among the different seasons was statistically significant. Further, seasonal variation in the relative abundance of the nymphs of A. sardeus in the field was corresponded with the pattern of hatching success in different seasons in the laboratory.
Impact of Influencer Market on Consumers of the Tourism Industry
Authors: Mohanty Rojalin , Samal Ansuman , Mohite Sagar , Shukla Shubhendu
Published: April 2022

This research has focused on the concept of influencer marketing and its impact on consumers of the travel and tourism industry. The goal was to find out whether travel and tourism companies through influencer marketing can attract consumers in this post-COVID situation or not. For this purpose, empirical data were collected from fifty social media users who are following at least one travel influencer on any social media site. From their responses collected by sharing survey questionnaire, it was found that most of the participants are not influenced by social media influencers in terms of deciding where they would travel.
Role of Mixed Inorganic Additives in Controlling the Dendrite Growth in Lithium Metal Anodes
Authors: H Irfan , A.M. Shanmugharaj
Published: April 2022

Here we demonstrate to suppress the dendrite growth and stabilize the LMA using Lithium difluoro(oxalato)borate (LiDFOB) and tetraethyl orthosilicate (TEOS) as primary and secondary additives in commercial LiPF6 salt electrolyte. While the incorporation of LiDFOB additive potentially reduced the overpotential values, thereby improving the cycling stability in comparison to commercial electrolyte in Li/Li symmetric cell, the performance characteristics dramatically enhanced on using TEOS as the secondary electrolyte additive. In addition, rate capabilities of the NMC/Li full cells are apparently higher on using the additives in the electrolyte system. The profound effect is attributed to the formation of film layer on the lithium surface, which eventually regulates the lithium deposition during the electrochemical cycling. Thus, incorporation of multiple inorganic additives in the commercial electrolyte system paves a way in making high performance lithium-metal batteries.
Optimization of Parallel Coupled Filter Using Genetic Algorithm for C Band Applications
Authors: Goyal Shally , Kushwah Dr. Vivek Singh , Thakre Dr. Vandana Vikas
Published: April 2022

PCML filter with five coupled lines is designed using mathematical calculations then the same PCML filter is optimized using GA for reduction in size and bandwidth enhancement. Optimized filter is compact and total size reduction is 37.66% after optimization and bandwidth enhancement after optimization is 84.3%. Both filters are useful for C band applications, wireless communication, satellite communication, cordless phones, surveillance, and weather monitoring using weather radar. The substrate used is FR4 epoxy with a dielectric constant 4.4 and thickness 1.6 mm.
Simulation and Comparison of Electrical Performance of Molybdenum Disulfide and Octadecyltrichlorosilane Self-Assembled Monolayer Based Nano MOS Device
Authors: B. Lakshmi Gayathri , M.K. Mariam Bee
Published: April 2022

The aim of this project is to simulate and analyze the capacitance and voltage characteristics of self-assembled monolayer MOS configuration and octadecyltrichlorosilane based nano MOS structured using different temperatures (100K-600K). Materials and methods: Two MOS capacitors Au/ODTS/SiO2/Si and Au/MoS2/SiO2/Si. These devices are designed and simulated using a multi dielectric energy band tool. The sample size for two MOS structures have been done and a total of 40 samples collected. The stack capacitances and gate charges for voltage ranging between -5V to +5V were obtained, tabulated, and plotted. Results: It is inferred that Au/ODTS/SiO2/Si has significantly greater stack capacitance with 2E-7 farad than the Au/MoS2/SiO2/Si 1.8E-7 farad. The independent sample T test has been analyzed and achieved significance of 0.001 using SPSS software. Conclusion: It would be prudent to conclude that self assembled monolayer based MOS were designed and simulated using a multi-dielectric energy band diagram program.
Comparison of VI Characteristics Between MOSFET and BIOFET by Varying Materials
Authors: R. Rajasekhar , Yakkala Bhaskarrao
Published: April 2022

The project aims to improve the drain characteristics of a novel device BIOFET by varying the materials like semiconductor and insulator in nanoscale. Materials and methods: The BIOFET and MOSFET was chosen as a group having 20 samples each respectively. The drain characteristics were simulated by varying the materials (semiconductor and insulator) of a BIOFET. Results: The analysis was found that BIOFET (mean-0.00013) is better compared to MOSFET (mean-0.000012). Conclusion: The Anova test was done which reveals that the MOSFET was found to be statistically insignificant (p-0.09) compared with BIOFET.
An Estimation of COVID-19 Confirmed, Death, and Recovered Cases Across India Using Novel Ridge Regularization and Comparing with Support Vector Machine
Authors: S Sreedhar , A Rama
Published: April 2022

COVID-19 is caused by Coronavirus, which leads to mild to moderate symptoms like cough and sneezing. It causes severe acute respiratory syndrome. India has the third highest number of COVID-19 confirmed cases in the world. The COVID-19 analysis was about the estimation of confirmed, death, and recovered cases across India. The aim of the study was to introduce the Novel Ridge Regularization model for effective prediction of COVID-19 cases, therefore reducing the overfitting of data. Materials and Methods: In this study, two groups were used for classification namely Ridge regularization with sample size of 110 and SVM (Support Vector Machine) technique with sample size of 110, similarly the dataset size of 65,896 was used for this experiment. Result: Based on the experiment, it was observed that the ridge regularization has got Least RMSE values than the SVM model with significance p=0.032. Conclusion: Ridge regularization model provides a better approach for analyzing COVID-19 cases than the SVM model.
Decrypting the Charge-Storage Properties of CeO2 Decorated α-Nickel Hydroxide in Battery-Type Supercapacitors
Authors: Wiston Biny R. , Tewatia Shivangi , Mahalingam Ashok
Published: April 2022

Usage of battery-grade Ni(OH)2 in combination with a highly stable electrode material can lessen the ion diffusion distance and boost charge-storage capacity. To acquire superior surface characteristics, electrochemically active lanthanide-oxide CeO2 is decorated over α-Ni(OH)2 using a simple, uncomplicated coprecipitation technique. The unique nanoarchitecture of Ni(OH)2 nanosheets embedded with CeO2 spheres promote ion/electron transit channels on the electrode surface, leading to excellent electrochemical charge storage. In specific current of 0.5 A g-1, the finest composite developed, attained a specific capacity of 257 C g-1 (960 F g-1). Owing to the evident improvement in the electrochemical activity of the synthesized CeO2-Ni(OH)2, it holds potential as electrode in futuristic battery-type supercapacitors.
Application of Thermo Acoustical Parameters for the Evaluation of the Available Volume of Ionic Liquid, 1-Butyl-3-Methylimidazolium Chloride in Mixed Solvents at Different Temperatures
Authors: Pattnaik Sudhansu Sekhar , Nanda Binita , Dalai Biswajit , Nanda Braja BANDHU
Published: April 2022

The available volume of 1-Butyl-3-methyl imidazolium chloride, [bmim][Cl] in pure water and aqueous solutions of potassium citrate and sodium citrate at different concentrations of solute and T = (298.15 to 318.15) K have been evaluated by making use of ultrasonic velocity and thermo acoustic parameters followed by a comparative study. The thermo acoustic parameters have been used to determine available volume, V
a for the solutions under analysis. For well understanding, the values of found from the thermo acoustic methods were tallied with the values found from the well-defined ultrasonic method (Schaaff’s method). The decrease of the available volume with an increase of the mass fraction of ionic liquid and temperature shows the existence of ion-solvent interactions of IL in the studied solutions. To the best of our knowledge, this study is a pioneering effort in the evaluation of available volume present in the investigated solutions by making use of the ultrasonic approach.
The UV Spectrophotometric-Based Analytical Method Development and Validation for the Quantitative Estimation of Passiflora incarnata
Authors: Singh Harsh Kumar , Nagpal Kalpana
Published: April 2022

Herbal products are an asset to mankind. We are utilizing them for ages for the treatment of ailments and the prevention of diseases further. For them to be consumed well, we must know the scientific evidence for their proper utilization. For them to be formulated effectively there must be a method for their quantitative estimation. One such extract is Passiflora incarnata, which holds immense potential in the treatment of central nervous system disorders and many others being an antioxidant. This is also known as Passionflower. The flower is collected, pulverized after drying the above-ground parts or its liquid extract is utilized for its medicinal effect. To utilize it well, we tried to develop a very reliable analytical method for its quantitative estimation
Accuracy Measure for Identification of Fake Blog Articles in Social Website Using Random Forest Over Naive Bayesian Classifier
Authors: CH Sai Krishna , G Divya
Published: April 2022

Aim: To identify fake blog articles that are posted in social media and avoid spreading of fake news in social websites using Random Forest over Naive Bayesian Classifier. Materials and Methods: Fake news is identified using Novel Random Forest (n=3) and Naive Bayesian Classifier (n=3). The performances of the classifiers are evaluated based on their accuracy rate using twitter media dataset. Results and Discussion: The accuracies of Random Forest (99.07%) and Naive Bayesian Classifier (89.40%) and statistical significance (p=0.00) are identified. Conclusion: Random Forest produces significantly better accuracy value than the Naive Bayesian Classifier techniques.
Design of Arrow Shaped Microstrip Patch Antenna for X and Ku Band Applications
Authors: .D Yuvaraj , Rao M .V Nageswara , P Shanmuga priya , S Naveneetha krishanan
Published: April 2022

A small size printed patch antenna to cover applications of X and Ku band is suggested in this paper. The suggested antenna consists of an arrow shaped patch on front view of FR 4 substrate and a partial ground on the other side. Initial design started with a rectangular patch of dimensions 10.7 mm x 7 mm. Then it is modified into arrow shaped patch in order to improve the reflection coefficient at lower and higher frequencies.The measurement of the antenna is 12 x 15 x 1.6 mm3. The antenna parameters are optimized using FEM based HFSS software. The operating range of frequencies include from 6.75 GHz to 18.96 GHz. The proposed antenna displays a good omnidirectional radiation pattern and maximum gain of 7.41 dBi at 17 GHz. Simulated S11 parameters, VSWR, gain, and current distributions are offered in this paper, and S11 simulated parameters are in good agreement with measured parameters.
Slip Effects on Unsteady MHD Free Convective Flow of Rivlin-Ericksen Fluid in the Presence of Heat Source/Sink
Authors: . Deepti .
Published: April 2022

In the present work, an investigation on MHD flow of viscoelastic fluid of Rivlin-Ericksen type across a semi-infinite plate in the presence of heat source/sink under free convection is conducted. The plate is moving with constant velocity subjected to periodic suction along with slip conditions. Further, the free stream velocity is taken of oscillatory in nature. The transport equations governing the flow are solved using perturbation analysis. The solutions obtained for the required fields viz. velocity, temperature, and concentration which characterizes the flow are discussed graphically for varying situational parameters appeared in the flow. The presence of heat source/sink in the vicinity of considered fluid has significant effect on the velocity near the plate. Further, the drag at the plate, Nusselt and Sherwood number, are evaluated for varying situational parameters which are compiled in the tabular format.
How Volkswagen Used Marketing to Regain Its Brand Image After the Cheating Emission Scandal: A Case Study
Authors: Odugu Rama Devi , Duttagupta Abhishek , Verma Siddharth , Kumar Tarun
Published: April 2022

The purpose of this research paper was to find out Volkswagen used marketing tactics to regain its brand image and trust of its consumes after the cheating emission scandal. After collecting secondary data, it was found that first of all, the management of the organization took all the right steps such as recalling all its vehicles installed with defeat device, compensating its consumers, apologizing to its consumers, and making huge changes in its existing business strategies. After that, the management of the organization created numbers of video ads and shared them to its different YouTube channels. The video ads emotionally struck its consumers. Besides, the organization also launched two new SUVs and started following a new strategy under which it decided to follow environmental sustainability. All these activities helped to the organization to win back its consumers and to regain its brand image.
Review on Biosensors: Fundamentals, Classifications, Characteristics, Simulations, and Potential Applications
Authors: Vinay Kumar Javalkar , N Shylashree , Srinivas Seema , Khosla Ajit , R Hari Krishna , C Manjunatha
Published: April 2022

Biosensor is a device which combines a physical transducer and biological active elements. The biological active element recognizes the specific analyte and produces biorecognized signal, which is further converted into a measurable signal by using an appropriate physical transducer. This review paper attempts in providing a comprehensive survey of the topic biosensor and due to its selectivity and sensitivity, biosensors are mostly widely used than other diagnostic devices. Because of its important features like selectivity, sensitivity, stability, reproducibility, linearity, and low cost, biosensors have a wide range of applications. This range includes their usage in disease detection, environmental monitoring, drug discovery, prosthetic devices, food safety, agricultural industry, and many more. Furthermore, this review discusses the various biosensors and its operations. Afterwards, with a summarized history of biosensors, further prospects have been described to present the usage of nanomaterials in biosensors. Various simulation software used to design the biosensor model are discussed in the end of the review.
Improvised Average Gradient for Predicting Multi-Traffic Scene Night Images Using Linear Regression Algorithm Compared with K Means Clustering Algorithm
Authors: Pavankalyan Pavan , B Vani
Published: April 2022

To improve the average gradient for predicting multi-traffic scene night images using linear regression algorithm. Materials and methods: Novel linear regression algorithm analyzes the correlation and extract texture features that characterize the samples. The novel linear regression algorithm and K Means clustering algorithm with samples N=10 is iterated 20 times for evaluating each group. Result: The fog images are recovered to clear image using linear regression algorithm with an accuracy of 95.02% and K means clustering with an accuracy of 92.82%. Conclusion: Within the limits of this study, the result proved that the novel linear regression algorithm has better accuracy than the novel K means algorithm. The statistical significance of accuracy value for the equal variance assumed is 0.05.
Remote Observing of Pulse and ECG Signal Using ESP32
Authors: N Divagar , M Prakash , J Niranjan Balaji , R Aathilingam
Published: April 2022

The paper depicts the advancement of gathering the heart rate of the patient checking framework dependent on the ESP32 module and AD8232 module. The framework design is shown thinking about WiFi, Bluetooth, and Bluetooth minimum energy association. The development of the proper model observation application implementation is shown. Force utilization estimations were performed. A short examination somewhere in the range of ESP8266 and ESP32 modules is given.
Metal Oxide Doped Egg Shell-Fly Ash Composite: An Effective Catalyst for Transesterification of Waste Oil
Authors: Devasthali Seema , Kulkarni Aparna , Bhatkar Neha , Sankpal Umesh
Published: April 2022

Biodiesel is a promising alternative for fossil fuels as it is a renewable source of energy and is considered a green fuel. Generally used method for preparation of biodiesel is catalytic transesterification. Fly ash, an inorganic waste, is a major environmental contaminant. The utilization and safe management of this material is the need of the hour. In this short communication, we report a composite of fly ash and eggshell modified with zinc oxide (ZEF) as a low-cost, efficient, and reusable heterogeneous base catalyst for transesterification reaction of waste cooking oil. The catalyst was prepared by the wet impregnation method and was characterized by FT-IR, XRD, and SEM techniques. Catalytic performance was checked in biodiesel preparation. Conditions like catalyst loading, oil: methanol ratio, temperature, and time were optimized. Product formation was confirmed by the GC analysis.
Design of Automated Health Monitoring System Using IoT
Authors: Varsha Julakanti , Sai Tarun Raj S , Krishna Chaithanya J
Published: April 2022

This project is designing of Automated Health Monitoring System Using IoT. Internet of Things (IoT) describes the network of physical objects, “things” that are embedded with sensors, software, and other technologies for the purpose of connecting and exchanging data with other devices and systems over the internet. By this system, people can monitor their day-to-day activities of health constraints and take necessary action in timely events. Further, the vital parameters of body should monitor always such as body temperature, room temperature, pulse counting, and heartbeat every day. As compared to existing one, the proposed design added with GSM and sound sensor. GSM sends the information to the family members with family doctor and notifies the consultant doctor for the medication in the individual risk factor. Any user can use this design. It is not limited to only patients and also no need to rush to hospital at regular intervals, at every time for the check-up, and do check-up safely at home. If any risk factor arises, one can visit the hospital.
Smart Automated Guided Vehicle for Flexible Manufacturing Systems
Authors: Adiga N Achal , Ballal Avaneesh B , P Dileep , M Harishgowda , T S Roopa , Angadi Gangadhar
Published: April 2022

In the Flexible Manufacturing System, automation and the ability to restructure the manufacturing facility is important. The development of a discretely working Smart Automated Guided Vehicle is the need of the hour. Hence the objective is to develop a compact unit load Smart Automated Guided Vehicle to increase efficiency and productivity & to overcome the problems of conventional material handling systems and improve the efficacy of manufacturing. Smart Automated Guided Vehicle is provided with navigation, weight sensing, obstacle detection systems with other auxiliary systems instrumental in zonal setup for the Smart Automated Guided Vehicle as well as adaptable for frequent changes. This model of Smart Automated Guided Vehicle is helpful for a small operational manufacturing unit for multipurpose applications at very low cost and high customizability. The objective is to provide a safe environment to the Smart Automated Guided Vehicle & its surroundings also, to reduce human dependency.
A Review on Advanced Monitoring and Identifying the Status of Grinding Machine Using Machine Learning Algorithms
Authors: P Suya Prem , Rajagopal Sivakumar , B Prabadevi
Published: April 2022

Recently, the development of the grinding process is improved by including automatic sensors, actuators, control systems, artificial intelligence, and industrial internet of things in the grinding machine. Already existing contact type techniques are replaced with the automatic sensor system to incorporate artificial intelligence in the normal grinding process. Therefore, optical and laser technology is emerging as a smart device to observe the surface topography of the grinding wheel, surface finish of the ground surface, and automatic dressing process. Moreover, artificial intelligence consists of machine learning, which teaches the grinding machine based on the existing data available to improve the quality and the production rate of the grinding process. This can be achieved by controlling the process parameter, monitoring the machine health, and attaining optimum condition. The present review paper addresses the existing problems associated with the contact type and non-contact type measurement. The study also emphasizes the importance of machine learning algorithms to predict the failure of the grinding wheel and surface roughness of workpiece material in the grinding process.
Metagenomics of Cariogenic Microbiota in Primary Teeth with Deep Dentinal Caries: An Illumina-Based Sequencing Study
Authors: Ramachandran Apoorva , Shetty Ashmitha Kishan
Published: April 2022

Discrepancy in the dynamic metabolic progression of the dental biofilm leads to dental caries, which is a polymicrobial infection. The homeostasis of the biofilm is unaffected and is not apparent unless there is an imbalance in the mineralization pattern of the supragingival biofilm. Literature provides numerous facts on microorganisms related to dental caries. Pathologic colonizers in the early stages of tooth decay involve organisms like Streptococcus oralis, subsequent adherence of Streptococcus sobrinus, and Streptococcus mutans[1]. Reports suggest the association of highly complex, variable, and uncultivable microbial population with dental caries, even though prime organisms are commonly known to be allied with disease succession. Association of mutans group streptococci and lactobacilli with the initiation of caries and early caries development have been well documented [2]. Studies have shown transition of early caries causing gram-positive primary facultative bacteria to anaerobic gram-positive rods and cocci and gram-negative rods as the lesion progresses to deep carious lesion[3]. Mapping of bacterial taxa revealed up to 14 phyla along with 101 genera. This comprised around 706 diverse OTUs (Operational Taxonomic Units). Caries progression at various stages and bacterial profile of different species associated with several disease have been observed. Some of the observed species found abundantly in whitespot lesion and dentin lesion of both dentitions were S. Parasanguinis and S. salivarius[4]. Molecular methods for bacterial identification and enumeration are performed routinely to precisely study bacterial species associated with dental caries, including those that are not presently cultivable.
The Mechanism of Spam Comment Detection Using Count Vectorizer and Naive Bayes Machine Learning Algorithms in Python
Authors: Puneeth M B , Ramakrishnan V
Published: April 2022

AbstractAim : The aim of this study is to predict Novel spam comments using Naive Bayes and SVM algorithms to improve the accuracy. Spamming is the process of posting unwanted and awkward comments on specific posts in any type of social sharing medium or video sharing medium. Materials and Methods : The Dataset used for training and testing of proposed text precision models is created using the comments of some popular videos from Youtube with 5 attributes and Sample size = 150. The framework that retrieves suitable data adapts SVM algorithm and compares it with Naive Bayes algorithm. Results and Discussion : The retrieval accuracy of SVM classifier is (96.72%) and Naive Bayes algorithm is (90.89%). There exists a statistical significant difference between SVM and Naive Bayes with (p<0.05) Conclusion : The work has confirmed that the efficiency of the support vector machine algorithm has given more accuracy when compared to the Naive Bayes machine learning algorithm.
Computational, Spectral, and Bioavailability Studies of Venlafaxine Cyclic Impurity
Authors: Sasidharan Pillai Anil Kumar , Bhaskar B L
Published: April 2022

Detection and qualification of process-related impurities assume importance in pharmacological drug development programmes. From time to time, preliminary investigations of such compounds might direct us to better drug options. Impurity profiling also tells us about the toxicity impacts due to the possible carry-over of such molecules into drug formulations. This paper depicts the structural and spectral investigation of 5-(4-Methoxyphenyl)-3-methyl-1-oxa-3-azaspiro[5,5]undecane (VEN-CI), an impurity associated with the anti-depressant drug Venlafaxine (VEN). The structural optimization was performed using Density Functional Theory and the computed data was then compared with experimentally derived data accessible in the literature. The chemical reactivity and stability of the title molecule were evaluated by assessing the HOMO-LUMO energies. The bioavailability and toxicity impacts were also investigated computationally to evaluate the medicinal chemistry friendliness.
Sustainability in Heavy Metal Bioremediation
Authors: Raghupathy Shwetha , Sundar Ranjitha Dhevi V. , Arunachalam Sathiavelu
Published: April 2022

Heavy metals are a major class of inorganic pollutants in the environment and are highly toxic, non-degradable and bioaccumulate. Removal of heavy metals in a green and sustainable way is essential. Plants and microbes assisted phyto or bioremediation can be integrated with their ability to produce useful green alternatives for renewables like bioethanol, biocrude oil, bioplastics, food supplements, biofertilizers, etc. Even though numerous lab-scale works are prevalent where organisms efficient in bioremediation have other beneficial qualities, implementations of the same on a natural environmental level are inadequate. Hence, there is a necessity to plan such operations to decrease the pollution levels and meet the demand in future to improve sustainability and meet the United Nations’ Sustainability Development Goals (SDGs).
Structural and Functional Characterization of Nano Formulated Lemon Oil and Aloe Vera Based Essential Oil Ingredients By DLS, SEM and FTIR for Biomolecular Interactions
Authors: Sravani Gurakala , S Thanigaivel
Published: April 2022

Aim:The major aim of this study is to identify the biomolecular interactions of nanoformulated essential oils. Materials and methods: Lemon oil and aloe vera nanoemulsion (N=12) preparation was done by standard protocol. It is further used for Particle size analysis in nanometre range, average mean diameter of particle size distribution and functional groups using sophisticated instruments like DLS, SEM and FTIR. Results:The results of this study has shown that average particle size of lemon oil and aloe vera nanoemulsion was obtained by DLS was 336±1nm, the mean diameter of the particle size was obtained by SEM was 42±2nm and in FTIR various functional groups were identified.Conclusion:The particle size analysis, average mean diameter of particle size and functional groups of nanoformulated lemon oil and aloe vera shows higher biomolecular interactions than the essential oils
A Method to Estimate Water Flow Rate Using Sound of Flowing Water
Authors: Wadhavkar Nitish , Pinge Soham , Jain Shubham , Rathod Surendra
Published: April 2022

With the population increasing exponentially, there has been a shortage of water in various countries. To help people manage water resources in an appropriate way, a water monitoring and management system needed to be built. Several invasive flow meters are present to cater to the problem but there exist several overhead expenses and issues with it. A good alternative for the above, a non-invasive flow meter, would be a more efficient solution. Though, some non-invasive flow meters exist, they’re expensive and unsuitable for use in some critical scenarios. So, a novel method and system, to calculate the rate of flowing water using audio-processing of the sound of flowing water, was developed. The system would be clamped on the surface of the pipe, unlike other systems which operate from inside the pipe. The flow meter developed using this method would only require a microphone on the sensor’s part, which will make it cost-effective. The process involves an algorithm that processes the sound of water using a microcontroller unit and then computes a single value which then depicts the range of flow rate. Further, using IOT analytics, future predictions and other important metrics would be displayed on a simple yet detailed user interface.
Structure Optimization and Electronic Properties of Co2tix(X=Si, Ge) Heusler Alloys: A DFT Study
Authors: Alhan Preeti , Kumar Suresh , Kumar Ranjan
Published: April 2022

A theoretical study of structural, electronic, magnetic, mechanical and vibrational properties of Co-based heusler alloys, namely Co2TiX(X=Si,Ge); have been studied by the first principle calculations with the Generalized Gradient approximation(GGA) based on Density functional theory(DFT). The total spin magnetic moments per unit cell is 2µB, obeying the Slater-Pauling rule. The electronic band structure along the high symmetry points reveal that majority spin states have metallic character and minority spin states have a band gap at the Fermi level. There are no imaginary phonon mode which illustrate the dynamical stability. The Bulk modulus, young’s modulus, shear modulus, Pugh’s ratio, sound velocities, Debye temperature in accordance with the Voigt-Reuss-Hill approximation. The elastic constant results show that these alloys are mechanically stable.
Fungi: The Assorted Bio-Remediators
Authors: Anand Raksha , Bharadvaja Navneeta
Published: April 2022

The most widely used eukaryotic model organism fungi, with its simple yet specialized organismal structure, possess the biochemical ability to degrade pollutants, therefore being of economic importance. Its bioremediation capacity is attributed to either its chemical modification mechanisms or influential bioavailability, with effects of degradation on metals, metalloids, as well as highly toxic radionuclides. Fungi form mycelial network extensions, their catabolic enzymes having low specificity, and can hence independently use pollutants as a substrate for growth. These features make fungi best suited for the process of bioremediation. However, fungi have been under-exploited for environmental bioremediation in spite of them being present as dominating creatures in the soil-living biomass and abundance in aqueous systems. Yeasts are very efficient in degrading wastes and can be easily engineered for targeted features. In this review, we will briefly discuss some of the potential “mycoremediation” techniques.