bluuebunny/crossref_metadata_2025 huggingface dataset:
Modes of Transmission of Novel Coronavirus (NCov)
Authors: Wagh Pankaj Wagh , Kanojiya Deepak R , Sarde Pratiksha V. , Fulzele Sapna M.
Published: April 2022

The global breakout in the new SARS-Coronavirus-2 have prompted many interrogations concerning this virus’s origins and spread. The already stated information of the modes based on transferal also measuring the efficacy in regards to prophylactic estimates will support within limiting this COVID-19 upsurge. SARS-Coronavirus-2 transmission mechanisms have now been identified as respiratory droplets, physical contact, and airborne. On the other hand, researchers are looking into some of the other possible modes of transmission with some studies showing that the virus spreads through feces-oral, conjunctival secretion(eyes), sexual transmission, mother-to-fetal transmission, surface contact, saliva, and asymptomatic carriers. The major goal of this review is to gain a better understanding of SARS-Coronavirus-2 transmission in addition to make exhortation for consist of along with avoiding the novel coronavirus. From its very beginning in Wuhan, China in December 2019, SARS CoV-2 has afflicted more than 31 million people worldwide, resulting in even more than 2 million fatalities. The world continues to be in the dark about a definite therapy for this extremely communicable diseases. Until then, we must depend on tried-and-true techniques to slow or prevent the spread of this viral disease, such as social withdrawal, hand cleanliness, and using a facial mask.
Mini Review of the Significance of Vitamin C in the Management of Novel Coronavirus
Authors: Bhoi Kavita , Paunikar Swapnil
Published: April 2022

A newly discovered COVID-19 is a communicable disease which is caused by coronavirus. The coronavirus disease 2019 pandemic has affected 100 million people in the world with just about 22,69,466 deaths occurred to date. In the management of COVID-19, Vitamin C has various physiological functions, many of which include immunomodulatory, antioxidant, anti-inflammatory, and antithrombotic functions. In the systematic review we reviewed the feasibility of accessible evidence on the significance of nutrient C in treatment of patients with coronavirus. Methods: Accessing the importance of Vitamin C in patients with coronavirus, we take already various research published articles, meta-analysis, systematic review, and randomized control trails on role of nutrient C. The Web of Science, Pubmed, and Scopus were obtained and using specified search query. For producing the graph and plots, we used the R-studio application.
Comparative Analysis Of CNTFET Based SRAM Cells
Authors: Valluria Aswini , Musala Surada
Published: April 2022

Due to the distinctive ability of retaining the data, SRAM is the most prominent memory element used in many electronic devices. The fundamental limits faced by the CMOS technology below 10nm, restricts its relevancy in terms of power consumption, size and speed. Therefore considerable concentration is focused on an alternate technology i.e CNTFET especially for low power designs. This paper mainly focuses on the comparative analysis of different CNTFET based SRAM cells like 6T, 7T, 8T, 9T and 10T. The comparison is done with respect to Power consumption, delay and Noise Margin.
Numerical Investigation of Boiling Flow in Oval Tube with Different Ellipticity
Authors: Liaw Kim Leong , Kurnia Jundika Candra
Published: April 2022

Improving heat transfer has been the continuous quest in thermal engineering field. With higher transfer rate required, many researchers have shifted their attention towards boiling heat transfer that offer superior transfer rate. Despite its potential, study on this heat transfer process have not been as extensive as its single-phase counterpart. Particularly, to the best of our knowledge, no study on the boiling heat transfer in oval tube with different ellipticity. Thus, numerical investigation using RPI wall boiling model and RNG k-ε turbulence model is conducted for different ellipticity of the oval tube. It is found that the heat transfer performance drops as the ellipticity increases with constant perimeter. Decrease of heat flux and increase of mass flow rate have positive impacts toward the heat transfer performance. The vapor generation resulting by the heat flux and mass flow rate is having high influence in the heat transfer coefficient and pressure drop.
Perfect Matching in Various Fuzzy Graphs
Authors: V Jesudas Selvaraj , C Y Ponnappan
Published: April 2022

An induced fuzzy sub graph  of a fuzzy graph G (V,E) is said to be a matching if every vertex of G (V,E) is incident with at most a vertex in . A induced fuzzy sub graph  of a fuzzy graph G (V,E) is said to be a perfect matching if every vertex of G (V,E) is incident with exactly a vertex in . In this paper we will define a perfect matching in fuzzy graphs. Further we investigate the bounds and properties of matching numbers in various fuzzy graphs.
Compressive Strength of Brick Masonry Confined with Glass Fibre Reinforced Polymer
Authors: Manasa A C , Basutkar S M , Madhavi K , Amalkar M. S , Renuka Devi M.V. , Jagadish K. S.
Published: April 2022

Compressive strength is one of the key factors influencing behavior of brick masonry. Various traditional techniques can be used to increase the strength, stiffness, and ductility of unreinforced brick masonry. However, considerable mass and thickness will be added to the original structural element as a result of with both aesthetics and economy will be affected. In this study, behavior of brick masonry prisms confined with glass fibre reinforced polymer (GFRP) has been investigated. Various patterns of wrapping were adopted using polyester resin. Maximum Compressive strength and ultimate strain of GFRP confined prisms were compared with unreinforced prisms. Results obtained show a substantial increase in compressive strength of prisms when confined with GFRP-polyester and GFRP-epoxy.
Experimental Study of Three Stream Coaxial Jets
Authors: Sundaram Rajkumar , Vasanthakumar Parthasarathy , Suseela Moorthi Aravindh Kumar
Published: April 2022

A core Mach 2 jet from the convergent-divergent nozzle in the presence of two coaxial sonic streams from convergent nozzles was investigated experimentally at different nozzle pressure ratios using visualization technique. The jet field was visualized using shadowgraph for nozzle pressure ratio (NPR) 3 to 6. From the visualization results, it was observed that the core length of Mach 2 jet for NPRs 3 to 6 increased with increasing coflow NPRs, indicating reduced mixing of coflow three stream jets as compared to Mach 2 jet (without coflows). From the present study, it was clear that the use of two sonic coflows on Mach 2 jet would result in core elongation for all the NPRs thus acting as a mixing inhibitor. But the sonic coflows were found to weaken the waves in Mach 2 jet, which is advantageous from the aeroacoustic point of view.
Reconceptualizing Empowerment and Autonomy: Ethnographic Narratives from a Self Help Group in South India
Authors: Babu Gloria M , Kumaramkandath Rajeev
Published: April 2022

The paper revisits academics’ conceptualisations of women empowerment as stopping short of autonomy. It departs from the general observation that women empowerment movements by and large have failed to translate the new agency of women outside the domains of socio-economy; that women empowerment movements’ capacity to re-engage with patriarchal structures and ideologies is seriously contained. Through an ethnography of Kudumbashree, an SHG in the South Indian state of Keralam, we question the neat distinctions between empowerment and autonomy that prevail in the academic common sense. The transition of agency from the economic to the political domain is a subtle enterprise and is mediated by a number of factors, including the awareness, economic independence, personal freedom, mobility, decision making capability, and political participation. Socio-economic and political implications of women empowerment could be the first step in challenging and overcoming the relations of oppression in any society. The stereotypical assumptions can be negotiated by solely apportioning responsibilities and re-engaging with the system through everyday practices. The ethnography rearticulates the subversive potentials of socio-economic forms of women empowerment. The nuances of empowered women’s re-engagement with local gender/power regimes lead to changes at the conceptual level that cuts beyond the individual and group level material transformations.
Feasibility Study on Amalgamation of Multiple Measures to Detect Driver Drowsiness
Authors: Bajaj Jaspreet Singh , Kumar Naveen , Kaushal Rajesh Kumar
Published: April 2022

Driver drowsiness is one of the major causes of road accidents which leads to fatal and non-fatal injuries, sudden deaths, and substantial monetary losses. Due to advancements in technologies like Artificial Intelligence (AI), various approaches have been carried out to detect driver drowsiness at the early stage. The existing measures comprises certain issues like intrusiveness, variation in results, and tested in simulated environment only. A hybrid solution is the need for early detection of drowsiness of driver by amalgamation of multiple effective measures. Many researchers have concluded that developing a driver drowsiness detection system by using hybrid measures would be more efficient and highly recommended. The main contribution of this paper is to evaluate and identify the effective measures to detect driver drowsiness and choose the best measures to combine. It will help in early detection of the driver drowsiness in a more efficient manner and avoid crashes on the roads.
A New Approach to Single Chambered Microbial Fuel Cell for Procreation of Bioenergy in the Treatment of Sugar and Dairy Wastewater
Authors: Umachagi Sunil , Paruti Mahantesh N , Vijayakumar Miryala
Published: April 2022

Pollution of water, waste disposal, and their management is big problem faced by the world today. Industrial waste, agricultural waste, and household waste are best substrates for energy generation. India is one of the leading producers of sugar and dairy products in the world. These industries discharge a bulk amount of wastewater per day without proper treatment during working seasons. Sugar and dairy industry wastewater has high COD and BOD, which is hazardous for aquatic life and human use also. MFC have earned importance in the last few decades due to its ability to generate bioelectricity from all renewable sources, Most of the MFCs have been used to treat different kinds of wastewater, such as sugar, dairy, brewery, domestic wastewater, distillery, rice mill, paper and pulp, swine wastewater, etc.
Gadolinium Nitrate Decorated Reduced Graphene Oxide Structure and Morphological Studies for Battery Applications
Authors: Nirlakalla Ravi , Surekha G. , Suvarna R. Padma , Krishnaiah K. Venkata
Published: April 2022

In-situ chemical and thermal reduction method was followed to prepare reduced graphene oxide (rGO) and gadolinium nitrate doped rGO (rGO/GdN) for XRD, FTIR, Raman, SEM, HR-TEM, and AFM investigations. From XRD, rGO/GdN composite was in nano crystalline structure with diffraction peaks 19.38o, 22.49o, and 31.59o correspond to (101), (201), and (111) planes. FTIR spectrum shown oxygen containing functional groups with vibrational bands of hydroxyl (-OH), carbonyl (C-O), epoxy (O-C-O) group, and a strong peak represents stretching vibration of Gd-O. Raman spectra provides appearance of D, G, and 2D bands at 1323, 1572, and 2662 cm-1 respectively. Moreover, an additional band at 1607 cm-1 revealed in rGO/GdN represents the existence of nitrogen. Crystal d-spacing from HRTEM of rGO is found to be 0.344 nm for (002) plane and for Gd was 0.283 nm for (400) plane. Morphology indicated that GdN with particles are well anchored on rGO sheets. Furthermore, AFM studies for thickness of rGO/GdN was estimated as 32 nm with Average Roughness and Root Mean Square are 15.19 and 23.16 nm respectively. Hence, rGO/GdN nanocomposite has prospective applications for battery owing to their smaller crystallite sizes.
Affine Transform Assisted Firefly Algorithm in Image Registry to MRI and CT Brain Images
Authors: B. Suresh Babu , Narayana M. Venkata
Published: April 2022

Medical multimodality images create an essential need of Image registration. In this work, we focused on one of the components of the methods of which is the measure of similarity used to match the images. We are particularly interested in the iconic approach, which takes into account only the information carried by the intensities of the pixels of the images to be recalibrated. This approach has the advantage of being fully automatic, since no prior segmentation is necessary. The main contribution of this research work is to propose new measures of similarity based on cumulants and the development of edge worth and for some of them they approximate the Mutual Information, which is a measure of similarity of reference in registration. Tests on these new measures show their effectiveness for registration medical images. In addition, the generosity of the proposed approach allows the use of these measures in various situations. Further we proposed and analysed a novel multimodal image registration method for medical imaging using firefly algorithm (FF). We optimized the registration parameters of affine transform with firefly algorithm to register computed tomography (CT) brain image over magnetic resonance image (MRI) to maximize mutual information. We tested our method over images of different sizes and modality.
An Overview of Spoof Detection in ASV Systems
Authors: Ravindran Swathika , Geetha K
Published: April 2022

In current years, voice based application are used broadly in varied applications for speaker recognition. By and by, there is a wide work in the investigation of parodying and against mocking for Automatic Speaker Verification (ASV) framework. The current advancement within the ASV system ends up interest to secure these voice biometric systems for existent world applications. This paper provides the literature of spoofing detection, novel acoustic feature representations, deep learning, end-to-end systems, etc. Moreover, it conjointly summaries previous studies of spoofing attacks with stress on SS, VC, and replay alongside recent efforts to develop countermeasures for spoof speech detection and speech sound disorder tasks.
Cell Envelope Thickening: A Mechanism of Drug Resistance in Mycobacterium Tuberculosis
Authors: Singh Richa , Varshney Itika , Chauhan D.S. , Prasad Tulika
Published: April 2022

Emergence of multi-drug-resistant (MDR) strains of Mycobacterium tuberculosis (Mtb) is recognized as an alarming threat to public health and it limits the number of compounds available for treatment of global tuberculosis (TB) epidemic. MDR is defined as resistance to at least two first line drugs, e.g. Rifampicin and Isoniazid, used commonly for the treatment of this disease. Multi-drug resistance may be due to presence of a thick, hydrophobic, impermeable, and waxy cell envelope (cell wall and cell membrane combined together). The present study investigated the cell envelope thickness in Rifampicin and Isoniazid resistant and sensitive Mtb isolates by transmission electron microscopy (TEM). Electron microscopic examination exhibited evident differences in cell envelope thickness between the sensitive (approx. 24 - 27 nm) and resistant (approx. 34 - 42 nm) Mtb isolates. Thus, this study demonstrated that thickening of cell envelope in resistant isolates might be one of the primary defense mechanisms adopted by Mtb against antibacterial drugs and the observed resistance towards Rifampicin and Isoniazid, the major first line drugs used against TB, might be attributed to this enhanced cell envelope thickness in drug resistant strains.
EFFECTS OF CENTRIFUGAL CONTRACTION EXERCISE OF RECTUS ABDOMINIS ON IDIOPATHIC LOW BACK PAIN AMONG HANDLOOM WEAVERS
Authors: L. Yogeshwaran , J. Suresh
Published: April 2022

Handloom weaving is one of the traditional cottage industry of India. The awkward and prolonged adaptation of malposture for a prolonged period of time to meet the job demands makes them vulnerable for musculoskeletal disorders where low back pain gains more attention due to the disability caused by it. Chronic low back pain not only causes discomfort, but also disrupts their productivity.
Analysis on Content Based Image Retrieval Using Image Enhancement and Deep Learning Convolutional Neural Networks
Authors: B.D.C.N . Prasad , Sailaja M. , Suryanarayana V
Published: April 2022

"Content-Based" means that an image contents search analyzes instead of meta data, including keywords, tags or image descriptions. The word contents could apply in this sense to colours, structures, textures or any details extracted from the picture itself. CBIR is desirable as searches relying purely on metadata depend on the quality and the completeness of annotations. CBIR method for the recovery of images from huge, unshaped image databases is commonly used. The CBIR method is used. Therefore, users are not satisfied with standard knowledge collection methods. In addition, there are more images available to users, as well as the advent of web creation and transmission networks. Consequently, there is a permanent and important output of digital images in many regions. Hence the rapid access to these enormous picture collections and the identical image retrieval from this broad image collection presents major challenges and demands efficient techniques. The efficiency of a content-based image retrieval system depends on the characteristic representation and similarity calculation. We therefore have a simple but powerful, profound, CNN-based, and feature-extraction and classification-based imaging system. Some promising results have been obtained from a range of empirical studies on a variety of CB IR tasks through the image database. Content-based image recovery systems (CBIR) allow you to find images identical to a query image among a picture dataset. The best-known CBIR system is Google's search by image feature.
Synthesis of Ni0.5Co0.5Fe2O4 Ferrite and Effect of Annealing Temperature on the Structural, Morphological and Dielectric Analysis
Authors: Kour Simrandeep , Mukherjee Rupam , Kumar Nitish
Published: April 2022

In the current work, we have synthesized nickel substituted cobalt ferrite nanoparticles using Pechini's method. The presence of single-phase synthesized nanoparticle is confirmed at annealing temperature around 1000 oC and the crystallinity nature further improves at 1150 oC. The average crystallite size is found to increase with increasing annealing temperature. The strain in the crystalline particles also found to decrease with increasing temperature as confirmed through XRD analysis. The cuboidal morphology with considerable size is observed in nanoparticles by FESEM images. The EDAX spectrum further confirms the presence of pure single phase of desired elements in grown nanoparticles. The dielectric properties were studied using impedance spectroscopy, recorded from 100 Hz to 1 MHz at room temperature for different annealed temperatures. The change in the frequency dependent dielectric properties with increasing annealing temperature are in accordance with the Maxwell-Wagner two layers model for space charge theory and correlated barrier hopping (CBH) model.
A Review On The Synthesis Strategies For The Fabrication Of Superhydrophobic Coating
Authors: Pusplata Pusplata , Tadge Prachi , Ray Sudeshna
Published: April 2022

Over the past few years, superhydrophobic coating exhibiting unique structure and exceptional water repellency has emerged as a versatile coating for the applications in the field of anti-corrosion[1], anti-icing 2], anti-fogging[3], self-cleaning[4], anti-fouling[5], and medical sectors. Recent progress in the underwater and flexible electronics, automotive, advanced textiles, high end footwear, and food packaging industry sectors are expected to act as crucial growth drivers of this superhydrophobic market in the future. Self-cleaning and water-repellent behaviors are governed by the ‘wettability’ of a material surfaces as naturally found in lotus leaf, peanut leaf, rose petals, poplar leaf, Salvinia molesta floating leaves, butterfly wing, fish scale, water strider, compound eyes of mosquito, gecko feet, desert beetles, spider silk, cactus, and many more. In general, to what extent a material is wet with a liquid is determined by the balance of surface free energy and roughness. With the advent of nanotechnology and nanomaterials, surface architecture as well as surface chemistry can be controlled to obtain superhydrophobicity. Surface chemistry alone may not be adequate to explain the superhydrophobic behavior. It appears to be a physiochemical phenomenon, where substrate is a function of two key aspects comprising surface chemistry and surface architecture. This can be achieved by incorporating lower surface energy species to the surface.
Assessing the Adsorption Capability of Nano SnO2, ZnO, and Its Composite for the Removal of Heavy Metal Ions
Authors: A Fathima Beevi , Sreekala G. , Beena B.
Published: April 2022

71% of the earth surface is covered by water. Out of which 97% of the water is found in the oceans and approximately 3% is available as fresh water. This accessible fresh water is polluted by different types of soluble and insoluble materials. One of the soluble materials is heavy metal ions. Both the substances can be separated by different methods at different rate. In this study, we assessing the capability of nano SnO2, ZnO, and its composite for the removal of dissolved heavy metal ions through adsorption. Also optimum adsorption conditions were determined with respect to pH, adsorbent dose, contact time, and temperature. The nano materials were prepared by green method. The techniques XRD, FTIR, SEM, and TEM were used for their characterization.
ANALYSIS OF MACHINE LEARNING BASED RENEWABLE ENERGY SYSTEMS
Authors: . K. DrParishVenkata Kumar , Arshad Mohammad , Hussain Md Ali
Published: April 2022

The present research focuses on the development and optimization of the particle swarm techniques inspired in nature to predict wind speed in renewable energies with real-time wind farm data structures, of unique machine learning architectures for neural networks alongside certain mathematical and stochastic populations. The research work in this article includes six modules, i.e., designing proposed architectures of the neural network with variants based on population stochastic particle swarm (SPS) optimization and developed mathematical parameters in place of hidden neuron numbers to effectively predict the speed of renewable energy systems that reach the set number of neurons. The wind farm data sets are used for training, testing and validation of the proposed model of wind speed predictors. The final prediction model proposed involves the applicability of a neural wavelet network for a predictive wind velocity and the mother wavelet function is used to allow the hidden neurons and to measure the wind speed output with the reduction of the set parameters.
APPLICATIONS OF MACHINE LEARNING ANDAUXILIARY TUMOR TREATMENT IN THE PROCESS OF MEDICAL RESOURCE ALLOCATION
Authors: V Prasad , Razia Shaik , Sridevi Gutta
Published: April 2022

In the last decade, machine learning has become very interesting, driven by cheaper computing power and costly storage—so that growing numbers of data can be saved, processed and analysed effectively. Enhanced algorithms are designed and used to identify hidden insights and correlations between non-human data elements in broad datasets. These insights help companies to better decide and optimize key indicators of interest. Machine learning is becoming more common because of the agnostic use of learning algorithms. The paper presents a number of machinery and auxiliary tumour processes to assign health resources, and proposes a number of new ways to use these resources at the time of artificial intelligence in order to make human life part of this process and explore the good conditions which are shared by both the medical and computer industries.
The Trending Role of Artificial Intelligence and Its Applications in Formulation of Solid Dosage Forms: A Review
Authors: Navya K. , Kamaraj R. , Bharathi M.
Published: April 2022

Artificial intelligence (A.I) is a technology based system involved in use of advanced tools and software’s and has achieved human level of capabilities and brought a paradigm shift in pharma industry therefore use of A.I in pharmaceutical product development has elevated over past few years. Adopting of technology can save money and time also provide good understanding between formulation and process parameters. Solid dosage forms are predominant in pharmaceutical market. It is estimated that tablets are the most come solid dosage form which contributes more than two-third of global market. Tablets are produced with many formulation factors i.e. from raw material to finished product therefore it is a great task and often complicated. Thus the use of A.I can help to obtain optimized formulations which could benefit pharmaceutical industry massively. Therefore adopting A.I–based technologies in manufacturing process of pharmaceutical product will improve the quality and safety of the product.
3D Printing of Capacitor Using Ionic Liquid Gel
Authors: Kobayashi Tatsuya , Watanabe Yosuke , Khosla Ajit , Kawakami Masaru , Shiblee MD Nahin Islam , Ogawa Jun , Nakamura Tensho , Harada Yuya , Yoshida Tsukasa , Furukawa Hidemitsu
Published: April 2022

In recent years, there has been a growing demand for safe soft robots that work in a work environment similar to that of humans. The use of 3D modeling technology in the manufacturing of soft robot chassis, soft electronic parts, and wiring processes is expected to lead to more efficient and smaller soft robot manufacturing. The objective of this study is to fabricate a gel capacitor using ionic liquid as an electrolyte, which has characteristics such as non-volatility, flame retardance, and conductivity. We fabricate ionic liquid gels that possess flexibility and conductivity after curing using a photoformable 3D gel printer, and discuss their performance as capacitors.
THE ANALYSIS ON APPLICATION OF IOT IN BIOMEDICAL INSTRUMENTATION
Authors: Ramana Lakshmi Adusumilli , Razia Shaik , Rao K Srinivasa
Published: April 2022

IoT-based biomedical applications are used in biomedical systems such as healthcare, diagnostics, prevention, therapy and monitoring. In addition, healthcare studies are moving toward individualised measurement as a whole. Observed assessments in the laboratory/clinic must be replaced by more comprehensive evaluations. But traditional barriers to long-term free-lived assessment have been the high cost and complexity of equipment. Due to the lack of supervised conditions in free-living assessments, environmental analysis is needed to provide context to individual measurements. Biomedical engineers should be aware of the opportunities, challenges, and limitations presented by low-cost and easily accessible Internet of Things (IoT) technologies. In our biomedical research project, IoT hardware and software technologies have been used to extract quantitative data for comparison with cloud-based cognitive information. A custom interface shows patient-specific information, pathology details and user interaction results to increase the user experience.
Graphite Counter Electrode for Cost Effective Dye Sensitized Solar Cells (DSSCs)
Authors: Karuppasamy B , Gayathri V.
Published: April 2022

Hydrothermally synthesized TiO2 nanoparticles were coated onto FTO glass plates and sensitized with Eosin Y (EY) dye. The graphite counter electrode (G) was fabricated by G coating onto the Al and then the cells were assembled by sandwiching the TiO2 photo anode (soaked in EY) and the counter electrode. The assembled FTO/TiO2+EY/Electrolyte/GCE solar cells were subjected to I-V characteristics under a light source of 100mW/cm2. I-V measurement was carried out for Pt CE, and for the G CE based DSSCs. The result cell with Pt CE shows high open circuit voltage (VOC
) 0.717V and fill factor (FF) 0.51, where the G CE based cell gives short circuit current (ISC
) 1.4 mA and photo conversion efficiency (η) 0.56%. Finally, the cell which is fabricated with G counter electrode shows better performance than the Pt CE based cell.
Design of Dual Transduction-Based CMOS-MEMS Electronic Stethoscope
Authors: Sundararajan Ananiah Durai Durai , R Pugazhenthi
Published: April 2022

The stethoscope provides primary information about the heart and the lungs. It enables rough diagnosis of the functionalities of heart and lungs of the human body through the pick-up of emitted sound from within them. Acoustic determination of the functionality of the critical organs must have high accuracy to reduce mortality rate. Manual examination and diagnosis with reliance on sound have poor reliability due to the nature of high interference causing inaccuracy. Second order harmonics are significantly high due to such interferences resulting in distortion. There is a need for technical advancement for efficient and seamless pick up of the bio-sounds. Existing electronic stethoscope design is cumbersome and uneconomical. A novel dual transduction technique is proposed in this CMOS-MEMS electronic stethoscope design, which produce high SNR value and high sensitivity. This proposed electronic stethoscope includes two microsensors, viz. piezoresistors and the piezoelectric device that provides high accuracy. Dual transduction enables pick up off of two bands of frequency that emanates the function of the heart and the lungs with great precision.
Comparative Study of Multimedia Question Answering System Models
Authors: Patel Hardik Bhikhabhai , Iyer Sailesh Suryanarayan
Published: April 2022

Question Answering Systems is a mechanized way to deal with finding right solution to the inquiries posed by human in their own language. The enormous measure of data returned by web crawlers like Google, Yahoo, and so on, clients are over-burden to track down the right data from the web search tools. This QA approach takes care of these issues. Rather than returning a rundown of reports and connections from the momentum web crawler, the QA framework gives data from a bunch of replied, alongside reasonable media information. Question answering procedures plans to exploit top to bottom etymological and media content investigation just as area information to return accurate responses to regular language questions. QA framework has rundown of boundary like: question size, m-dimension, technique count, answer cardinality, and answer range. This paper investigates the advancement of mixed media question replying research, their plan boundary, and subtleties its future perspectives. Multiple Line Questions and Video Question Answering methods have been discussed at length and their performance measured on QA framework parameters.
Identification of the Quality of Tea Leaves by Using Artificial Intelligence Techniques: A Review
Authors: Gaba Ira , Ramamurthy B
Published: April 2022

This paper summarizes the outcome of the survey carried out for quality identification of a tea leaf and eventually price prediction. Quality identification can allow to categorizing leaf in different grades, which helps the buyer and seller to acquire suitable quality to their need. Price prediction is an important feature, which can bring certainty at price and farmers can be benefitted more for their reasonable good quality. Additionally, if the leaf disease is identified at the initial stage that would also allow farmers to timely resolve the concerned issues and save their corps. In the field of agriculture, this has been always a research area to identify and predict the quality of tea leaves. Various artificial intelligence techniques are hot topics in the field of recognition and their effective combination cannot only solve the problem but also enhance recognition accuracy. Therefore, there is an imminent need for a detailed survey on compiling techniques used for the identification of different varieties of tea plants. In this research, we aim to propose a review of the various techniques which can be utilized for determining the quality and price prediction. The survey is hybrid in nature with a combination of different artificial techniques, which is a suitable approach to target effective tea leaf identification. Further for the classification of tea leaf images, various algorithms can be combined as well to obtain better results and different algorithms can be used for feature extraction on the basis of texture extraction, color extraction, and shape extraction.
Augmented Reality Sudoku Solver
Authors: G M Ananya , Kumar Singh Ankit
Published: April 2022

Solving Sudoku puzzles is now made easy through a few mobile applications. However, these applications fail to provide a fast and accurate solution. Computer Vision and Deep Learning have advanced to a level where another dimension for solving such puzzles has been added. The paper aims to propose a novel method to generate the solution of Sudoku puzzles and to display it using Augmented Reality. The Sudoku puzzle is recognized over several image processing phases, followed by recognition of letters using Deep Learning. The captured puzzle is then solved by a solver written in Rust. Eventually, the resultant mask of the solution is merged with the original image by computer vision and uses Augmented Reality to render the solution. The end-to-end pipeline takes milliseconds before an accurate final solution is obtained. The solver is extremely reliable in terms of precision and speed.
Fingerprint Recognition Based on Deep Learning Pre-Train with Our Best CNN Model for Person Identification
Authors: Shinde Krishna K. , Kayte C. N.
Published: April 2022

In this article, we use pre-train VGG16, VGG19, and ResNet50 with ImageNet wights and our best CNN model to identify human fingerprint patterns. The system including pre-processing phase where the input fingerprint images first technique apply cropping and normalize for unwanted part remove of fingerprint images and normalize its dimension, second Image Enhancement for removing noise in to ridgelines, and last Canny Edge Detection technique for adjustment to smooth image with Gaussian to remove noise. Then apply one by one model on KVKR fingerprint dataset. Our best CNN model has automatically extracted features and RMSprop optimizer use for classification this features. This study performing experimental work of each pre-processed dataset and testing these three models with different dataset size of input train, test, and validation data. The VGG16 model got a better recognition accuracy than VGG19 and ResNet50 models.
Impact of COVID-19 Induced Lockdown to Sustain Employee Performance Management Systems in NCR Corporates
Authors: Gupta Neelesh , Chaturvedi Pooja , Pathak Ravindra
Published: April 2022

All hell broke loose in the corporate world in March 2020 when India went under total lockdown in a matter of days. The equation between work (what), worker (who), and workplace (where) was altered at the fastest pace in human history. This paradigm shifts also coincided with the appraisal/year end cycle. Most of the Indian corporates follow the financial year cycle (April to March) for their annual performance appraisal/management process. The human resources department was at the forefront of every board room’s agenda within the corporates of the National Capital Region (NCR) of India. The challenging and interesting part about life of an HR professional is to help business take the hard decisions in the most objective yet humane way possible. Therefore, perhaps rightfully, there wasn’t one single solution or a clear thought process emerging across participating organizations. And to borrow from Gabriel Garcia Marquez, “Our code of ethics supposes that we doctors are made of wood.” There is similar thinking on HR as well. Hopefully this time it will not be so. This paper presents an overview of the changes to the PMS system and its outcomes undertaken by HR managers in corporates of NCR. HR managers of 117 corporates were surveyed through a structured questionnaire between the period 5th April, 2020 through 15th April, 2020. The main objective of this publication is to document and contribute to the body of knowledge changes that were introduced due to an unforeseen calamity.
Optimization of ANN Architecture and Training Parameters Using Taguchi Method
Authors: Vora Manish Jashvantrai
Published: April 2022

Artificial neural networks (ANNs) have gained significant popularity for modeling and optimization. Choosing appropriate training and design parameters for an ANN, on the other hand, is still a difficult task. These parameters are typically chosen by a trial-and-error strategy in which a large number of ANN models are developed and compared. This evidence stated how the Taguchi approach can be used to enhance an ANN model. To show the technique, a case study of a minimization of Green Sand-casting defects in a green sand-casting process is provided. Total 175 samples were taken for the study. L18 orthogonal array was used to construct the ANN training and architectural parameters. A Taguchi-optimized ANN model was created and showed excellent prediction accuracy. Analyses and experiments have shown that the best ANN training and architectural parameters may be found in a systematic manner, minimizing the time-consuming trial-and-error method.
When Worlds Collide: Using Films to Understand the Heterotopic Overlaps of Multiple Worlds
Authors: Borah Rashmi Rekha , G Bhuvaneswari , Hussain Moon Moon
Published: April 2022

Heterotopia is an idea as put forward by Michel Foucault, from the notion of place and non-place as disruptive elements. This article explores the fascination with Foucault's brief and sketchy idea of heterotopia in the context of cinema. We examine how the elements of heterotopias are most productively understood through the narrative of popular cinema as quintessential traits of film industry across the globe. Films like Caparhnaum, Fahrenheit 451, Interstellar, Stalker (1979), Avatar, Gulabo Sitabo(Hindi) and many more are examples of heterotopic films. These films stimulated utopian as well as dystopian affects in their audiences. The notion of heterotopia has been extensively deployed in media studies. In this paper, we discuss Caparhnaum and Fahrenheit 451 as a richly heterotopic films in which cinema worked with spaces within spaces. Using the heterotopic dichotomy the authors examine filmmaking as it reconstructs the simulated spaces. The authors also want to underscore, in cinema, what the space consists of, who occupies it, and in what ways.
Agricultural Waste Materials Applications in Building Industry – An Overview
Authors: K Anitha , S Senthilselvan
Published: April 2022

Agricultural wastes have become a growing concern in recent years as the world's population has grown. Agricultural solid wastes are irresponsibly dumped or burned in public areas in several countries worldwide, resulting in air pollution, soil contamination, and smoke. The residue could end up in a water supply, polluting the water and aquatic ecology. Agricultural waste is crushed and turned into fine and coarse aggregates, or it is burned into ash, which is used in the making of concrete. Agricultural solid waste is a lightweight aggregate used in the production of masonry blocks [1]. Green concrete's thermal insulation, sound absorption, water stability, fire resistance, and mechanical properties will all be improved as a result [2]. The present paper explores the various structural components prepared by using agricultural waste materials, such as bio-bricks, natural fiber components, lightweight concrete, green concrete, concrete roofing, and tile components.
Pre-Tensioned CFRP Tubes for Improved Energy Absorption
Authors: Gattiineni Venkateswarlu , Nathi Venukumar
Published: April 2022

The use of materials like CFRP has shot into prominence to achieve lightweight designs without compromising on structural integrity. Circular thin tubes are often employed in passenger cars as energy absorbers to absorb the impact energy during an accident. When such tubes are made of materials like CFRP it contributes to weight reduction besides leading to reduced fuel consumption. Also due to their lower weight, such tubes shall be capable of absorbing more energy per unit mass compared to metallic designs, which is defined as specific energy absorption capacity (SEA). Pre-stressing techniques are widely used by civil engineers across the globe to impart more stress/energy bearing capacity for the structures. Based on pre-stressing principles, the introduction of pre-tension during the fabrication stage for thin CFRP tubular structures has been experimentally studied to validate the applicability of pre-stress concepts for more SEA. The study investigates experimentally the additional advantage prestressing can bring for a CFRP tube in terms of SEA improvement.
A Study on Perception of Online Education
Authors: Ubeja Satnam Kaur
Published: April 2022

Pandemic COVID-19 has created problem for the whole world in many folds. People have lost their lives and there has been an economic crisis in the families and in all sectors. This pandemic has not only affected livelihood, but students have been affected badly. Especially school children have not experienced their study in a proper way during pandemic because they could not meet their classmates and there has been no interaction with the teacher. In a similar way, college students have not felt that good as they could not go to college for studies and they had no face to face interaction with faculty. College teachers were missing their students as education was through online only during pandemic. Since teaching had to continue in this time therefore, government has taken a good initiative that online teaching is a boom at this point of time for uninterrupted teaching. Despite of few cons of online education, this online education has made many teachers tech savvy and increased market value of teachers and their confidence got boosted. Still online education is playing a very important role in current education. This paper is an attempt to see students perception towards online education in Madhya Pradesh State. 114 completely filled responses were received and reliability analysis, t test, Anova were applied to test the hypotheses.
A Comprehensive Analysis of Technologies for Accounting and Finance in Manufacturing Firms
Authors: Jayesh G. S. , Novaliendry Dony , Gupta Shashi Kant , Sharma Amit Kumar , Hazela Bramah
Published: April 2022

Technologies are helps to keep the data flows, monitoring and maintain the employee records safe. In this work discussed about the present new technologies, which is the cloud, artificial intelligence, big data, and Blockchain new accounting technology. Technology allows enterprises to operate with reduced workforce efficiently and effectively and helps reduce operational costs. Technology provides accurate and reliable immediate financial results thanks to its ability to eliminate mistakes and to reduce human interventions. In certain parts of the world, the old way financial reporting has changed, while in other parts it is evolving gradually. But how technology affects processes of financial reporting worldwide. This paper aims at research and analysis of the processes of financial reporting that have resulted in transformation technologies.
Intelligent Traffic Control System Using Deep Learning
Authors: T M Inba Malar , G Bharatha Sreeja , M Amala Justus Selvam , E Jemima Sharon , K Jeevitha , R Keerthi , R Mahalashmi
Published: April 2022

Traffic congestion and regulating traffic in traffic signals are major issues in cities. Nowadays, in most of the cities, traffic management centers installed numerous cameras all over the roads and traffic signals. Such cameras can be effectively used for the automation of traffic signals. The objective is to develop a real time system that can automatically monitor real time traffic and make the system intelligent using artificial intelligence techniques. Specifically, Deep Convolutional Neural Networks are employed to perform the task. From statistical traffic data, it determines count, type of vehicle, average speed, distance between vehicles, etc. Based on traffic, the algorithm instructs to stop vehicle or queue or move. It can also record a wrong-way driver. Using license plate recognition, security applications such as unauthorized vehicles are identified. If there is violation of traffic rules, they are recorded with registration number. It can detect ambulances and give first preference. The proposed algorithm identifies VIP vehicles and clear traffics in automated ways. Ambulances are given priority to pass the road. The entire system have been developed using a standalone-Graphical User Interface (GUI). We have implemented successfully and the proposed framework performs satisfactorily.
Design of Load Balancing Technique for Cloud Computing Environment
Authors: Shivaliya Shikha , Anand Vijay
Published: April 2022

Cloud computing allows for the provision of IT resources on-demand and has various advantages. Because the majority of firms have shifted their activities to the cloud, data centers are frequently flooded with sporadic loads. When dealing with high network traffic in the cloud, it is necessary to balance the load among servers. This is something that load balancing can help with. The primary goal of load balancing is to distribute demand evenly among all available servers such that no server is under or overloaded. Load balancing is the process of dispersing load among several nodes to make the best use of resources when work is overwhelmed. When a node is overburdened to support the load, load balancing is essential. When a node becomes overcrowded, the load is dispersed to the remaining optimal nodes.
Factors Influencing Customers’ Loyalty Towards Offline and Online Stores
Authors: Khatri Sakshi , Parekh Minal , Mashru Meena
Published: April 2022

Loyalty is the key to long term success. As the economy and market are changing, in reference to internet and mobile technologies, shopping behavior of the consumers has developed more complex behavior because of the variety of channels emerged and offering variety of choices and options and this brings changes in consumer buying behavior. With this note, the researchers try to find in this study how the consumer decides their purchasing channels and their loyalty towards the company they opt for. The primary data is gathered by means of structured questionnaire from 50 respondents living between Kandivali to the Churchgate area. In the study, the researchers have analyzed the customers’ loyalty towards the offline and online company they shop. The data for analyses are taken from the purchases made in the same city and over the same period of time.