bluuebunny/crossref_metadata_2025 huggingface dataset:
Kai and Zen: Effective Tools for Improving Productivity and Quality: A Case Study of an Indian MSME
Authors: Bubber Deepak , Babber Gulshan , Jain Rakesh Kumar
Published: April 2022

Old manufacturing methods have become obsolete and are ineffective in the current era of highly competitive global markets. The customer expectations have seen a dramatic shift in tastes and preferences due to large product availability that keeps on improving with time. Nowadays companies are forced to adopt new manufacturing methods that facilitate growth, notably lean manufacturing tools, and related techniques have seen a positive acceptance worldwide. Furthermore, kaizen is one of the effective tools that are based on the principle of the right use of workers’ potential and capabilities. The present case study is done in an industry engaged in manufacturing child parts which are used in gearbox assembly, transmission, hydraulic lift assembly, etc. for original equipment manufacturers. Henceforth, these issues formed the basis for the current study. Furthermore, a road map was developed that was based on understanding the current manufacturing process, thorough analysis of records, followed by detailed employee interviews. Moreover, this study used a kaizen approach that involved people from the shop floor that lead to many positive suggestions and practical implementation. Finally, this study successfully improved overall product quality and met customer expectations without any major financial investments. The positive findings of this case study saw tangible gains in the form of Withdrawl Nut P252006 additional rework cost reduced from 5.82% to 0.41% and in-house rejection (scrap) cost reduced from 0.84% to 0.03%. Pre Loading Nut P124034 additional rework cost reduced from 5.97% to 0.34% and in-house rejection (scrap) cost from 0.89% to 0.02%.
Underwater Wireless Sensor Networks with Energy Efficient Routing Protocol Using Load Balancing Technique
Authors: Bapu Tapas , S Pradeep , V Nagaraju , Nagappan Partheeban , N Sankarram , Sriramulu Srinivasan
Published: April 2022

Underwater Wireless Sensor Networks is effective and intelligent utilization of energy for routing protocol in longer network lifetime. Energy Consumption and load balancing are the vital roles for a network lifetime. The use of load balancing in WSN is granted as the best resource of sink mobility which protects energy sources to organize. The aim of this paper is to evaluate various deployed strategies involving sink mobility. Multiple mobile sinks are capable of performing computational operations like collecting information from electric joints instantly, storage and also communication capability. It evaluates the results and the effect of sink mobility by comparing with another routing protocol GEDAR.
GAMAN – Genetic Algorithm in Mobile Adhoc Networks for Creating Systematic QoS
Authors: Bapu Tapas , R Anitha , S Soundararajan , V Nagaraju , Nagappan Partheeban , A Daniel
Published: April 2022

MANET is a mobile adhoc network that is made of several mobile nodes that can communicate in multi-way without any fixed or regular infrastructure. Due to its special features, such as its self-organization, easy deployment it has been preferred for many military and civil applications. MANET has also gained popularity in the multimedia field. MANET has certain levels of requirements, such as QoS (Quality of Service), jitter and energy, bandwidth, and end-2-end delay. MANET’s one of the basic requirements is having QoS and should have efficient routing to support other applications. In this research paper, a special Genetic Algorithm known as the GA algorithm based on routing on a mobile adhoc network is designed and termed as GAMAN. The proposed model uses a 2 QoS system for routing. The outcome of this paper showed that the GAMAN method is a significant one for QoS in MANET.
Facile Synthesis and Structural, Microstructural, and Dielectric Characteristics of SnO2-CeO2 Semiconducting Binary Nanocomposite
Authors: Kumar Aashish , Chitkara Mansi , Dhillon Gulshan , Kumar Naveen
Published: April 2022

Polycrystalline (1-x)SnO2-xCeO2 nanocomposites, where x = 0, 0.05, and 0.10, were synthesized using conventional co-precipitation method without any traces of impurities. Structural characterization revealed that the composition with x = 0 exhibited single-phase tetragonal rutile symmetry, whereas for x = 0.05 and 0.10 compositions showed both tetragonal and cubic phase coexistence as confirmed by Rietveld refinement studies. HRTEM micrographs showed nanoscale formation of nanocomposites and also displayed fringes depicting d spacing (110) = 0.34 nm belonging to SnO2 crystal matrix and d spacing (111) = 0.31 nm for cubic CeO2 crystal lattice. Dielectric properties of host SnO2 nanoparticles were improved by CeO2 addition in the SnO2. The increment in the real part of dielectric permittivity was observed for CeO2 modification of SnO2 matrix.
Assessment of Organophosphate Pesticides Residue in Groundwater of Kota Region of Rajasthan, India
Authors: Sheikh Samrin , Kuldeep Kuldeep , Mathur Anil K. , Kamboj Pawan
Published: April 2022

Pesticide use in agriculture has the potential to contaminate groundwater supplies. In reality, according to studies, only about 0.1 percent of toxins widely used in agriculture reach the target insect. At the same time, the rest enters the environment inappropriately and contaminates soil, water, and air, poisoning or harming non-target creatures. Organophosphorus pesticides (OPs) were widely used when organochlorine pesticides were prohibited from using in the 1960s and 1970s due to their harmful effects. This study aimed to measure the extent of organophosphate pesticides pollution in the groundwater of the Kota region. Contaminant compounds of several organophosphate pesticides have been identified in the groundwater of the Kota region.
Electrochemical Studies of Novel Clay-Conducting Poly-o-Toluidine Hybrid Nanocomposites for Supercapacitor Application
Authors: R Baby Suneetha
Published: April 2022

Nanostructured composite of poly-o-toluidine (POT) with novel clay mineral identified from Tuticorin in Tamilnadu, India, known as Indian clay (IC), were synthesized by simple, inexpensive chemical oxidative polymerization. The structural, thermal, and morphological characterization of the composites showed formation of nano scale, thermally stable composites with intercalated semi crystalline nature having features of both POT and IC. Thermal stability was found to be more for the composite with 0.5g of clay loading. Cyclic voltammograms for the nanocomposite modified glassy carbon electrode showed well defined redox couple at 322.7 and 3.8mV indicating not only the conducting nature but also the good electrochemical stability of the material. The value of specific capacitance of 280Fg-1 at a scan rate of 50mV/s proves the high capacitative nature of the nanocomposite. EIS gave the Rct and Cdl values as 240.1ohm and 23μFcm-2 respectively making it a promising supercapacitor electrode material.
Studies on Leak Detection in Process Pipelines Using Artificial Neural Networks/Machine Learning
Authors: N Harshitha , Meda Ujwal Shreenag , Rao Padubidri Ashwin , Hulake Vinayak
Published: April 2022

In process industries, leakage in pipelines is common and an environmental, health and economic issue to be addressed without fail. To detect the presence of leaks in pipelines, there are several conventional leak detection techniques that are available. From the literature, conventional leak detection techniques can be mainly classified into: hardware-based, visual and software-based methods. Researchers have focused more on software-based methods due to simple and reliable operation. Under software-based methods, using machine learning algorithms that is a data driven approach for leak detection and localization is becoming popular because of learning capabilities. Therefore, in this review, several recent conventional leak detection methods and artificial neural networks/machine learning based leak detection methods are described. It is an attempt made to identify leak detection techniques along with the common methodology followed for building a leak detection system using artificial neural networks/machine learning.
Impact of Social Accountability and Responsibility Through Education and Environment
Authors: Mathur Sandeep
Published: April 2022

This research paper is based on a fieldwork project, undertaken by the group of volunteer students in collaboration with Indian Development for Human Care (IDHC Society), India. Slums are a global phenomenon that may be witnessed in nearly any city on the planet. Children from low-income families who live in slums are deprived of numerous essential facilities that non-slum children enjoy in general, therefore they require special attention. We as a team started the research by understanding the work and establishing good relationships with the staff and students to comprehend the way of their working in a better way. We were introduced to the youngsters with whom we will be working for their better future. We started by teaching them basic English, mathematics, basic habits, personal hygiene. We decided to plant trees as a good environment is necessary for our well-being. In this research work we spread awareness in our neighborhood regarding planting trees and keeping the surroundings clean. Also, spread awareness regarding COVID-19 to underprivileged children.
Identifying Factors Influencing Purchase of School Books in India: Identifying Role of Attitude, Trust, and Aspiration
Authors: Madan Hardarshdeep Singh , Tandon Urvashi
Published: April 2022

The objective of this study is to explore the intellectual development of consumer behavior in purchase of school books through previous published research studies. We try to explore as to what will be those factors that will directly have an impact on the purchase making decisions of the consumer i.e., the purchase intentions of print books. The constructs identified from the study shall provide significant insights to marketers to define and operationalize different strategies specially in education publishing industry which today stands at several thousand crores. This would also help them to understand as to what drives the consumers purchase intention in lieu of school books.
A Semiotical Case Study of the Unconscious in the Works of Salvador Dali
Authors: Singh Gandi Pankaj
Published: April 2022

This research paper attempts to analyse the contents of the unconscious (psyche) in the works of the Surrealist artist, Salvador Dali, and also to provide for an interpretation of the same. In order to establish a relation between psychology and art, Jungian symbolism is studied and to avoid any subjective approach to analytical interpretation, Semiotics of Charles S. Peirce is applied with respect to the whole work of art as a semiotic sign.
Photocatalytic Cementitious Materials to Reduce Air Pollution: Review
Authors: Kumar Pavan , Meda Ujwal Shreenag , K C Sachin , . Radhakrishna
Published: April 2022

Oxides of nitrogen (NOx) are highly reactive and major air pollutants generated from the vehicular emission and burning of fossil fuels in industries. These pollutants will create tropospheric ozone, formation of urban smog and occurrence of acid rain, etc. A potential solution for this would be heterogeneous photocatalysis. Using photocatalysts such as titanium dioxide (TiO2) inorganic and organic matter present in the air, such as NOx and VOCs can be adsorbed and oxidized by the action of ultraviolet (UV) light (sunlight). This technology is promising for cities with highly congested areas having high ground-level pollutant concentrations. Self-cleaning and air-purification coating with a super-hydrophilic photocatalyst (TiO2) coated on buildings can bring down the NOx concentration in the air. In addition, the incorporation of TiO2 in the form of nano-particles into cementitious materials will enhance their mechanical properties. This study evaluates and highlights the applications of nano titanium dioxide and its effects on the fresh and hardened characteristics of the cementitious composites.
Predicting Air Traffic Density in an Air Traffic Control Sector
Authors: Asirvadam Tina Vimala , S Sonali Rao , T Balachander
Published: April 2022

Air traffic over Indian skies continues to increase rapidly and due to this increased demand, efforts must be made to efficiently balance demand with capacity. Air traffic flow management is a concept that allows for better demand and capacity management. It helps airlines plan routes and schedule flights. The ability to estimate the volume of air traffic is hence a critical element in flow management. Determining traffic in an ATC sector necessitates a thorough examination of various hidden parameters. The prediction is carried out using machine learning algorithms, Recurrent Neural Network, and Long Short Term Memory that examine the data and find a pattern which then anticipates the traffic in the sector at any given moment in the near future. Given the real-time data and experimental findings from this study, it is clear that Long Short Term Memory provides a clearer indicator of the study's goal.
Collaborative Social Media Marketing in Small Scale Business Using Artificial Intelligence
Authors: Rani Vosuri Sandhya , Sundaram N
Published: April 2022

Technological progress causes structural changes in company strategies and business models, while effectively meeting customer and improving the cognitive ability of organizations. Through this advanced technology firm has to create a knowledge-based environment, which acts as a significant source for competency in the industry. In business environment, Artificial Intelligence (AI) has emerged as advanced technology to promote marketing practices through social media. However, adoption of artificial intelligence is relatively difficult to small business units rather than large firms. Small businesses need to focus on Artificial Intelligence-based social media marketing and investments in AI. Previous research has focused on implementing artificial intelligence in marketing, but very few studies focused on the AI-based social media marketing for small businesses that gives scope for present study. Therefore, present paper emphasized on AI-based social media marketing, challenges, and benefits for small businesses and explores the possibility of implementing AI.
Reactive Power Injection to Grid Using Transformer-Less MOSFET Based Single Phase Inverter Using PV to Achieve High Efficiency
Authors: M Vinil , G Ramya , M Moovendan , J Ajay Daniel
Published: April 2022

The transformer-less inverter has an increasing demand due to its low cost, high efficiency, and reliability. The elimination of transformers from grid connected PV enables to create the leakage currents across stray capacitance, which is connected between PV and the ground. To overcome this disadvantageous issue, the topology used is a single step conversion process of directly connecting coupled inductor to the grid. The efficiency and the quality of AC output current is improved by implementation of high frequency PWM switching commutation to the converter. The proposed system is focused to inject reactive power to the grid, changing the controlling techniques used for the Gate Pulse input, and reducing the number of switches, passive elements, and harmonics. It has an overall efficiency of 98.04%, higher than those of existing converters.
A Critical Analysis of the Regional Trade Agreements Among One Belt One Road Nations
Authors: Manzoor Hajra , Mir Parvez Ahmad
Published: April 2022

Using the structural gravity framework, this paper estimates the effect of three important concepts in the international trade flows between One Belt One Road (OBOR) countries. These facets have been previously discussed separately in the literature: the partial equilibrium effects on international trade flows of regional trade agreements, intranational trade, and international borders. The methodology used in this paper yields econometrically plausible and robust estimates of the impact of regional trade agreements (RTAs) on bilateral trade among the member countries by accounting for distance puzzle and several sensitivity analyses, such as endogeneity, phasing-ins of the RTAs, reverse causality, multilateral influences, and various estimation techniques. This study confirms that by taking globalization effects into account, the impact of RTAs on trade among OBOR countries becomes negligible. Also the declining effect of international borders on trade flow among OBOR countries suggests that the trade is facilitated more between the open economies.
A Matrix-Based Homomorphic Encryption for Preserving Privacy in Clouds
Authors: Mittal Sonam , Sharma Shagun , Ramkumar K.R.
Published: April 2022

As huge data need to store on clouds for big data analytics and related features to analyze data computationally. Cloud computing serves many services to the client over their data such as data storage, analysis, and different resources. To avail such services over clouds, client needs to provide the access to cloud service providers (CSPs) over their data, which leaves data unprotected and confidentiality of their data is at stake. Different techniques are proposed to preserve the privacy and confidentiality of client’s data. One of the most common is, cryptography, which converts plaintext to unreadable form that is ciphertext. But almost all the existing cryptographic techniques are not up to mark and don’t have potential to perform the computation on the ciphertext. The recent trends in field of cryptography, the homomorphic encryption is emerged as a boom, which enhance the privacy of data to a large extent, without compromising the confidentiality of users’ data at cloud end. Homomorphic encryption provides the ability to perform computation on encrypted data, even when data is in use. Most of the existing homomorphic encryption algorithms are having high computational and time complexity. In this paper, an enhanced homomorphic encryption algorithm is proposed specifically for the cloud environments, having better performance. In this paper, an enhanced homomorphic encryption algorithm is proposed specifically for the cloud environments, may having better performance. The algorithm uses prime number-based matrix for encryption and decryption. The algorithm may give better performance in terms of encryption, decryption, and overall execution time.
Brand Influencing Customers Buying Behaviors: A Case Study on Nike
Authors: Saini Mankeshva , D Saravanan , Kutty Noora Mohamed , Agrawal Raju
Published: April 2022

This research has focused on Nike and its strategies that are helping the organization to influence buying behavior of its consumers. For this purpose, this research has collected data from two credible websites. After collecting data from these two websites, it was found that Nike’s activities to influence buying behavior of its consumers completely depends on things such as new product development, customer engagement, and marketing. By collecting information from customers, such as their needs and expectations, the organization is developing attractive new products. On the other hand, through Nike+ website and by remaining active on social media sites, Nike is continuously communicating with its customers and is developing a positive relationship with them. Besides, through collaboration with third party companies such as Google, Nike is creating exciting ads that are alluring consumers towards the brand. Besides, by creating different social media pages for different brands, Nike is ensuring that it is connecting with consumers with different interests. Besides, Nike has continuously improved its products by collaborating with athletes and by introducing new technologies. These are the factors which are ensuring that consumers remain loyal to the organization to continuously buy from the organization.
Convolutional Neural Network Based Plant Nutrient Deficiency Detection
Authors: M Sowmiya , S Krishnaveni
Published: April 2022

Nutrient deficiency is a condition in plants in which the plant lacks particular amount of nutrients which are essential for the healthy state of a plant. In this paper, an automated nutrition deficiency detection system has been proposed using Convolutional Neural Network. Spatial information in an image is obtained by using Convolutional Neural Network. The proposed system can identify if the following nutrients: nitrogen, phosphorus, and potassium, are present in proper amounts and holds an accuracy percentage as high as 95%. The final output is an user interface which is made very simple and reliable for the farmers to understand. Just by providing the respective input image, the farmer gets to know what nutrient deficiency the plant is suffering from and also the remedial measures he can take to overcome it. The system also displays the threshold percentage for each of the nutrient deficiency, i.e. the percentage below which the plant starts suffering from each particular deficiency. This system aims to serves as effective tool for nutrient deficiency detection.
The Need for Conservation of Archeological Heritage, Current Challenges and Forthcoming Approaches
Authors: Kalla Ruma
Published: April 2022

Heritage is complete assortment of our inherited traditional values, culture, objects & monuments. Highly valuable is the array of contemporary behaviors, consequences, and actions that we inference from them. However, the archaeological sites are areas that provide information and materials about the distant past of mankind. The relevance of heritage is not limited till the past, but it also portrays our present and influences the future. Survey results and informatory from around the world shows that cultural heritage sites not only promote social cohesion, conservation, inherit skills and impart education, but also enhances infrastructure development, job opportunities, FDI, and economic growth. In this paper the need, process, significance, and values of archaeological sites has been discussed by considering appropriate case of Qutab shahi tomb Archaeological Park which is a recent example of conservation & restoration study and represents that the project is economically feasible for public access.
Stabilization of Sand Dunes with Recron Fiber and Cement Kiln Dust.
Authors: Chahar Vinay , Prasad Chandra Deo
Published: April 2022

This research study aims to stabilization of sand dunes by mixing locally available waste material i.e. cement kiln dust and recron fiber. The stabilization of soil program have been taken into two phases. First mixing sand dune with recron fiber with varying percentage from 0 to 2% by weight. In the second phase the optimum mixture obtained from first phase is mixed with cement kiln dust by varying percentage from 0 to 10%.From the experimental study it is observed that optimum quantity of 1.5% recron fiber with 7.5% cement kiln dust is found to be the most efficient for the stabilization of sand dune. The results shows the significant increase in the strength properties of the sand dune. The angle of internal friction of the soil is increased by 35% andthe CBR of the soil is improved by 77% in comparison to virgin soil.
IoT Data Analysis Using Different Clustering Algorithms: A Survey
Authors: Das Prabhat , Bora Dibya Jyoti
Published: April 2022

There has been a major change in the rise of data creation and consumption due to the quick development of contemporary technology and the advent of the Internet of Things (IoT). With this shift comes a significant challenge in data management, with the goal of extracting useful information and patterns from the vast amount of unstructured IoT data. However, due to some limitations, we are still encountering issues and challenges in obtaining patterns and meaning information, and thus formulating a research agenda to get a sense of the challenges that one might encounter while conducting research on clustering of this massive chunk of unstructured IoT data. In light of these considerations, this study looks at some clustering methods that may be utilized when working with unstructured IoT data.
Single-Use Plastic Packaging and Food and Beverage Industry's Take on It
Authors: Mishra Sneha , Fukey Leena N , Wankhar Varynia
Published: April 2022

Microplastics created by the gradual breakdown of SUP in oceans have recently been consumed by marine organisms, including fish, shellfish, etc. It is causing significant disturbance to marine life. The environment is littered with food packing. Snack food packaging is a great example of a long-standing, aesthetically obnoxious form of pollution. The majority of SUPs, especially perishable products, wind up in landfills within months of purchase. This is due to a rise in on-the-go food and beverage consumption, fueling the proliferation of single-use plastic packaging. The lack of dumpsters in some areas might contribute to an increase in littering. While the majority of food packaging plastics end up in trash, municipal waste, landfills, and even the seas, a tiny fraction can be recycled. The reason for this is that poor countries have a prevalent culture of human waste.
Impact of Service Quality and Patient Orientation on Loyalty Through Mediation of Patient Satisfaction
Authors: Dogra Ajay Kumar
Published: April 2022

Unprecedented disruption to growing service sector because of COVID-19 pandemic has put extra burden on an overstretched healthcare sector globally. Understanding changing dynamics and changing patient behavior is needed for survival of hospitals. Present study intends to find relationship between patient orientation, service quality perception, patient satisfaction, and patient loyalty. A descriptive research-based study design was adopted to collect data from 500 patients of 10 multi-specialty hospitals located in north India. To understand relationship between variables and cause and effect chain, PLS-SEM technique was adopted. Findings of the study found significant impact of patient orientation on satisfaction and service quality. Patient satisfaction was a strong determinant of loyalty. Mediating effect of satisfaction between quality and loyalty, and that of quality between orientation and satisfaction was also confirmed. Study concluded that increased satisfaction among patients can be achieved with help of a patient centric approach and quality service delivery.
Assessing Satisfaction Behaviour of Maternity Patients at an Indian Hospital
Authors: K Vinay Kumar , Ankiisetti Ramachandra Aryasri
Published: April 2022

Patient satisfaction is essential to evaluate the medical care and quality of care of a healthcare provider. An empirical study was undertaken to understand the satisfaction levels of patients at a specialty maternity hospital by analyzing the feedback of patients recorded after delivery. The findings suggest that core service offerings affect the overall satisfaction level of patients to a greater extent than non-core offerings. This result was proven using Multiple Regression Analyses.
Forecast and Analysis of Stock Market Volatility Using Deep Learning Algorithms
Authors: Nayak Pratham , Suresh Shravya
Published: April 2022

Stock markets serve as a platform where individuals and institutional investors can come together to buy and sell shares in a public venue and ultimately impact the economy. With the advent of digital technology these markets or exchanges exist as electronic marketplaces. These markets are very volatile thus making the stock market prediction a highly challenging problem. These predictions of stock value offer great profits which serve as a huge motivation for extensive research in this area. Identifying and predicting a stock value beforehand by even a fraction of a second can result in very high profits. Similarly, a near to precise prediction can be extremely profitable in the amortized case. This attractiveness of finding a solution has motivated researchers in both industry and academia to devise techniques despite the complications due to volatility, seasonality and time dependency, economy, and other such factors. Lately, AI/ML techniques like Fuzzy Logic and Support Vector Machines (SVMs) have been used to arrive at different solutions. In this paper, we explore and develop an ensemble predictive system to forecast the market prices using deep learning algorithms. Here we consider the fractional change in stock value and the intra-day high and low values of the stock to train and employ a neural network for obtaining the trading strategy that leads to relatively superior market returns. The focus here is on the use of regression and LSTM based deep learning strategies used to predict stock values. Factors considered are open, close, low, high, and volume.
Behaviour of Dune Sand Reinforced with Crushed Grains of Sanitary Ceramic Waste
Authors: Dave Mayank , Solanki Deepanshu
Published: April 2022

Research work was taken up to cope the major environmental problem of sanitary ceramic waste, which is assumed to be 9 tons per year (waste), and dune sand, which is a cohesion less soil and of no use due its low engineering properties. The sanitary ceramic waste is major environmental problem. This study gives the best use of the waste and making the best usage of the unused soil. Properties such as strength, stiffness, compressibility, permeability, swelling potential, frost susceptibility, water sensitivity, and volume change tendency may be changed by various methods of soil stabilization. A serious problem of dispose of sanitary ceramic waste is being faced by sanitary ceramic industries and construction industry. Dune sand mixed with crushed grains of sanitary ceramic waste can be utilized for various constructions and can be used further in construction of roads. Standard proctor test and CBR test were performed at various composition mix of ceramic waste into soil sample at given MDD.
A Machine Learning Methodology for Diagnosing Chronic Kidney Disease
Authors: A Abirami , S R Adharsya , K R Deepitha , S Kanaga Suba Raja
Published: April 2022

Chronic kidney disease is otherwise known as chronic kidney failure or chronic renal disease is a worldwide issue which causes the kidney to get damaged and it eventually leads to gradual loss of the purification function of blood which has to be done by the kidney, causing multiple complications as well as death rates. This failure of kidney is mentioned as “chronic” because the kidney will get damaged in due course of time, may be in a month to years. So, if the process of filtration and purification gets stop or slower, eventually it leads to the storage of waste matters, by the by it causes other indirect problems as well, such as development of kidney stones, heart disease, etc. People who are suffering from diabetics or high blood pressure are most probability get affected by this chronic renal disease. If the disease gets to its final phrase, the only way to save the patient is to make kidney transplantation or dialysis. Because this disease usually has no recognizable symptoms in the early stages, patients may be unaware of it until it's progressed to chronic kidney disease. Some commonly known symptoms pointed out by the experts are swelling of anklets, legs and feet, feel of itchiness at back of arm, inadequate sleep, toughness in breathing, nausea and vomiting. Early diagnosis allows patients to take action to help avoid chronic kidney disease.
Impact Assessment of Tropical Cyclone Tauktae on Coastal Region of Gujarat, India
Authors: Keriwala Neha , Patel Anant
Published: April 2022

Tropical cyclones are among the most destructive forces on the globe, and their powerful winds, high devastating storm surges, and major flooding are all capable of causing widespread devastation. A sudden intensification to a severe cyclonic storm occurred when Tauktae began to parallel the coasts of the Indian states of Kerala, Karnataka, Goa, Maharashtra, and Gujarat. Tauktae made landfall on May 17, 2021 in Diu, Gujarat. This article incorporates an overview of effect on severely impacted area in the Gujarat due to Tauktae. Around 64 people died in Gujarat as a result of the devastating Tauktae cyclone. This study seeks to identify who might be at risk in various situations. This study's findings will be beneficial to officials in the field of disaster management as well as those in determining how to minimize the loss of life and property during cyclones in India.
Enhancing Time Synchronization for Home Automation Systems
Authors: Mehta Kapil , Kumar Yogesh , Aayushi Aayushi
Published: April 2022

Clock synchronization techniques are in highly demand for smart home applications with the approach of the Internet of Things (IoT). The developing innovation of smart home applications built on the Internet of Things is generally constrained and scattered. Synchronization is the basic characteristic of the emerging field of IoT in smart home applications which is recommended for improving the acceptance and its use. For the clock synchronization between systems, Network Time Protocol (NTP) is used. But due to inconsistent routing and limited computing resources there can be the dominant source of error that limits time transfer uncertainty. This paper proposes an Elastic Timer Protocol for home automation system networks that performs better in terms of consumption of energy and time of convergence than other clock synchronization protocols. The proposed protocol improves the elasticity and efficiency of the network, resulting in a faster network convergence time. Furthermore, simulation results revealed that the proposed work has improved performance metrics and proved superior performance characteristics when compared to standard synchronization protocols.
Determinants of a Cross Border Merger and Acquisition Decision: A Literature Review
Authors: Chugh Sukhmani Bhatia , Goel Archana
Published: April 2022

This paper aims to explore, consolidate, and comprehend the determinants that impact a cross border merger and acquisition decision. We mainly research past studies performed in the last decade that have identified several factors affecting the merger decision. By integrating the research findings from prior research, we propose developing a clear understanding of the factors that determine a merger decision. Many factors like characteristics of the CEO of the target and the acquiring company have also been summarized in this paper, which have not been consolidated by previous studies. Studying the market and economic conditions of host and home countries can provide an insight into the investment decision. This can apprise policy makers, investors, and stakeholders to work on policies and regulations that would boost inward and outward deals.
A Survey of Optical Character Recognition Techniques on Indic Script
Authors: Chirimilla Ramya , B Vishnu Vardhan
Published: April 2022

Optical Character Recognition (OCR) is a technique that converts printed text and images into a digitized form, which can be manipulated by a machine. It has many application sectors like Banking, Financial, Legal applications, etc. Initially researchers were addressed and proposed many algorithms in image processing for character recognition and mapping. Most of the researchers focused on the Latin script English as it was supported by the Encoding standard ASCII. Later, people start realizing that OCR techniques for other languages are also gaining momentum these days. With the advent of technology and Unicode revolution, native language-based OCR solutions started emerging. In this paper, we aim to focus on the latest machine learning techniques applied on OCR for the language English and two languages from Indian continent were presented. Out of the two Indian languages, one is the stroke-based language, i.e. Hindi, and the other being cursive script-based language Telugu.
Ultra Wideband Planar Monopole Antenna with Pair of C-Shaped Slots and T-Shaped Sleeve for Microwave Systems
Authors: Matta Lovish , Sharma Manish , Kaur Parminder , Sharma Bhanu
Published: April 2022

This paper introduces a compact UWB planar monopole antenna for microwave imaging systems. An antenna consists of square shaped radiating patch with a couple of C shaped slots for exciting resonance. By introducing T shaped sleeves on the ground plane, wide impedance bandwidth is achieved in range of (3.6 - 12 GHz). The proposed antenna has compressed size having dimensions Ls× Ws× Hs mm3. By embedding C-shaped slots with varying dimensions on radiating patch additional resonance are excited which results better wide impedance bandwidth. Simulated results such as return loss, gain, radiation pattern authenticate the convenient antenna structure for different microwave imaging system applications.
Effect of Antioxidant on ROS Mediated Antifungal Action of ZnO Quantum Dots in Candida albicans
Authors: Chand Preeti , Pal Singh Surinder , Prasad Tulika
Published: April 2022

Nanomaterials are increasingly used as new paradigm for treating infectious diseases, wherein redox perturbation using quantum dots (QDs) show tremendous potential in eliminating various multi-drug resistant microbial pathogens. Herein, spherical, monodispersed ZnO QDs of ~5-6 nm size was synthesized. These ZnO QDs significantly inhibited growth of C. albicans cells. The antifungal action of ZnO QDs against C. albicans involved oxidative stress, mediated via augmentation of endogenous reactive oxygen species (ROS). Further, endogenous ROS production by ZnO QDs and their effect on fungal cell killing was investigated in the presence of antioxidant, ascorbic acid. Results showed that antioxidant failed to offer complete protection against ZnO QDs mediated oxidative stress. It is speculated that intracellular ROS alone is not the only mechanism responsible for ZnO QDs mediated microbial toxicity and other mechanisms probably act either in coordinated or parallel manner to induce cell killing, which merit further investigations for medical adoption of ZnO QDs in biomedicine.
Improving the Interpretation and Understanding of Web Traffic Time Series Forecasting with Statistical and Neural Network Models: A Machine Learning Approach
Authors: A Srilakshmi , A Srilakshmi , K Geetha
Published: April 2022

The time series forecasting is a sequential event used for predicting future events based on historical time-stamped data. It relies on various statistical models to fit into the historical time-stamped data and uses them to predict future observations. Web traffic is a major issue as this can cause setbacks to the workings of major websites. Mainly wikipedia gives a decent growth and it contributes to economical growth. Since the volume of users visiting a website has increased exponentially these days, the management of web traffic is an important consideration for the flawless functioning of a website. Statistical models such as ARIMA, ETS, and NNAR play a vital role in prediction of unknown data from the historical data. The proposed model is intended to reduce RMSE and there by maintaining accuracy as well. The proposed model is developed by extracting important features using hybrid feature extraction methods. Then those features are used to predict the time series by feeding optimized LSTM model and finally compared with statistical models.
Action Research for Continual Improvement of Online Learning of Kindergarten Students at Chitkara International School During Covid-19
Authors: Sood Parul , Thapa Alka , Sharma Nidhi , Kaur Navdeep , Chitkara Niyati , Chitkara Honey , Kaur Prabhjot
Published: April 2022

This study examines the effect of strategies adopted by Chitkara International School for the continuous improvement of online learning of kindergarten students, during the transition of classes from offline mode to online mode. The objective of this study is to increase the interest of the students in online classes, to increase the engagement of the parents in the child’s learning process, and upskilling the teachers for handling online classes during COVID-19 time. The study was conducted on 373 kindergarten students, parents, and 25 teachers of Chitkara International School. The study was conducted using pre-test/ post-test single group design. The sample was analyzed based on the qualitative and quantitative data. The findings of the study reported that there was significant improvement in the attendance of the students of the kindergarten classes, the cooperation and involvement of the parents increased, and there was a significant increase in the participation of the students in all the activities. This study was conducted with a purpose of providing quality education to students even during COVID times and all efforts were made in sync with the Sustainable Development Goal 4, which focuses on quality education.
Applications and Blockchain Solution for Big Data Challenges
Authors: Verma Hemant , Arora Priyanka
Published: April 2022

The term “big data” is related to data that is huge in amount, fast to access, or complex. A huge amount of data is generated day by day. The big data and its analysis play an important role in the world of IT with other applications like cloud computing, data mining, IoT, etc. As the internet and digital technologies are growing, the amount of data is also increasing day by day. But this amount of data cannot be processed by using traditional methods. A lot of effort is required to analyze this amount of data. But while ensuring data security and privacy, many challenges are there like protection against security breaches and data leakage, vulnerabilities in public databases, and third-party data sharing etc. The objective of this paper is to discuss various applications and security issues with blockchain solution of big data challenges.
Secure Coding and Software Vulnerabilities in Implementation Phase of Software Development
Authors: Khurana Mehak
Published: April 2022

The methodology in software development has shifted from waterfall to agile, which has earned appreciation as cost-effective development due to its speedy software delivery, under limited time constraints. At the same time, cyber attacks have become more surreptitious that are pretending threats to software. Security elements and practices in software development phases eliminate software vulnerabilities. Vulnerabilities happen in the software due to the unavailability of security practices during the levels of software enhancement. Software development using secure coding practices can resist the software from exploitation. Thus, the paper focuses on the detailed view of security weaknesses in the implementation stage of the software development life cycle (SDLC). The paper explains the non-compliant codes which expose vulnerabilities that can benefit the attackers to gain unauthorized access, therefore providing the mitigation to furnish a complaint code resistant to exposure. Both secure and vulnerable features can be curved from the source code. This paper concentrates on the human aspects of software security, including human actions and motivation. This paper enables us to learn about and promote secure coding standards for frequently used programming languages, regardless of the device used for programming.
Awareness and Attitude Towards Digital Screen-Based Binocular Vision Therapy Amongst Eye Care Practitioners of Karnataka
Authors: Hegde Namratha , Bandamwar Kalika , Annapurna Maram , Murali Kaushik , Rao Diwakar
Published: April 2022

Amblyopia interferes in the critical period of visual development among children. Due to the limitations of conventional management of patching therapy, in the recent decade digital screen based binocular vision therapy was introduced. We aimed to study the awareness and attitude of eye care practitioners towards digital screen based binocular vision therapy in management of amblyopia. The study has been conducted by constructing and validating a questionnaire. The questionnaire was validated through a pilot study. Around 104 eye care practitioners responded to the survey, showing 96% of the eye care practitioners’ awareness towards refractive correction as the first line of management for amblyopia. A high number of respondents (83%) were aware of prescribing computer-based video games for amblyopia therapy in the clinical practice. 'The visual function improvement is very much feasible with digital screen based binocular vision therapy’ was the opinion of 55% (n=52) of eye care practitioners.
Sentiment Analysis on Social Network Data and Its Marketing Strategies: A Review
Authors: Dash Priyanka , Mishra Jyotirmaya , Dara Suresh
Published: April 2022

Any social media plan should include the creation of sticky content. Marketers produce viral content in the expectation that it will go viral rapidly. The main issue is that influencer marketing efforts are difficult to track and might have catastrophic ramifications. Sentiment analysis may be used to assess influencer marketing efforts and assist brands in making educated decisions. The goal of the study is to determine how effective an influencer is at creating or boosting intangible assets, as well as to provide practical data for brands looking to hire the ideal influencer for their products. The nature of the research study is conceptual. The researcher analyzed and drew conclusions using secondary data from reliable secondary sources and conceptual demonstration. The next consistent promoting field is social media. Currently, Facebook dominates the advanced advertising area, closely followed by Twitter. Despite the evident benefits that these platforms provide, sites such as YouTube and MySpace are less popular. We investigate the effects of various internet promotional efforts on brand awareness. The purpose of this research is to see how social media sentimental analysis affects business growth. To investigate the audience's reaction to the brand in order to develop a fresh marketing strategy. To investigate the impact of a social media campaign on the target audience. With knowledge of the public's opinion toward a product or service, one can decide to buy. By processing and analyzing public sentiment received from internet reviews and social media, the polarity of the sentiment can be determined.
Use of Dyes As Photosensitizer in Photo Galvanic Cell for Conversion and Storage of Solar Energy
Authors: Singh Gautam
Published: April 2022

Abstract: The impact of photogalvanic cells containing the best combination of dyes, reductants, and surfactants was studied. The photosensitizers employed in this research were Methyl Orange-Glucose-Cetyl Trimethyl Ammonium Bromide, Thymole Blue-Glucose-Cetyl Trimethyl Ammonium Bromide, Victoria Blue-Glucose-Cetyl Trimethyl Ammonium Bromide, and Methyl Orange-EDTA-Cetyl Trimethyl Ammonium Bromide. Cell efficiency also has been reported to be significantly higher. The device has a conservation efficiency of 0.55 to 1.01 percent and can be used in the dark for 32 to 68 minutes. Various factors which influence solar energy conversion efficiency are also evaluated and accounted for.Key words: Potentials at power point, Photosensitizers, Rates of generation, Reductants, Fill Factors, surfactants, Power consumption, Charging time.GOAL 7: Affordable and Clean Energy