bluuebunny/crossref_metadata_2025 huggingface dataset:
Mobile Based Application on Weight Control Among Overweight Children
Authors: Dhiman Ranjana , Kumari Vinay
Published: April 2022

Childhood obesity is a common social problem of this century, especially in urban settings. Overweight and obesity are the 5th driving risk for disease worldwide. The aim of selecting this topic is social changes given diet, lifestyle, and physical activities by the development of a user-friendly yet handy, useful tool against childhood obesity. A quasi-experimental research design will be used. Subjects will be allocated to intervention and comparison groups by convenience sampling technique. The pre-test will be taken on the 1st day, the 1st post-test will be taken on the 30th day and the 2nd will be on the 90th day. Anthropometric measurements, CDC growth chart, children physical activity questionnaire, and children nutrition questionnaire were used to collect data. A schematic differential satisfaction scale will be used for the satisfaction of parents. If the intervention will give effective results, it may apply in child care to combat childhood overweight and obesity.
Mobile Augmented Reality Elements and Social Media Usage on Smart Tourism in Penang: Malaysian
Authors: Abumandil Mohanad , Ekmeil Fawwaz Abdel Rahman , Younus Ahmed Muayad , Alkhawaja Maha Ismail
Published: April 2022

This study is important after the COVID-19 pandemic and the great loss that occurred to the tourism sector in Malaysia in general and in particular in Penang, which is one of the most crowded tourist areas with hotels and is considered a major destination for tourists coming to Malaysia. This study is to provide an explanation of the current situation. Moreover, the study key contributions are these variables in the study that can affect the smart tourism with these elements mobile augmented reality elements and social media usage. Moreover, while adding to the body of knowledge, this research has practical and educational consequences for all travel agencies, potential customers, government officials, and the long-term sustainability of smart tourism. The research also attempted to emphasize the need of smart tourism adoption. Services that are smart tourism is a community service that provides visitors and the rest of the world with smart services, such as tourism and smart travel. In smart services tourism, this service will benefit tourism stakeholders as well as tourist attractions. Services highlighted are smart tourism online interactive, content display information such as list of tours in register culinary, handicrafts smart services tourism, performing arts area, tourist villages, and supporting other tours are interactive and informative ICT-based services in the form of smart tourism online interactive, and content display information (tariffs, pricing, hours of operation, contact person, and rating visitor).
Thermomechanical Properties of Artificial Muscle Based on Silicone-Carbon Fiber Composite
Authors: Dimitriieva Polina , Doroshenko Tamara , Fedoryak Alexander , Dimitriev Oleg
Published: April 2022

In this work, we demonstrate a novel prototype for a composite artificial muscle where specific filler is used to improve its mechanical and thermal conducting properties. Specifically, the muscle is based on the composite of silicone rubber and carbon fiber. The latter serves for reinforcement of the mechanical strength of the elastomer and improvement of its thermal conductivity for thermo-mechanical applications. Our studies show that both extent and orientation of the carbon fiber load in the polymer matrix influence the extent of the sample deformation. Particularly, it is demonstrated that the relative deformation of the sample can reach up to 7% upon heating to 70-80 0C and this deformation exceeds that measured in the unfilled reference sample by a factor of 2. We also demonstrate that, depending on the fiber orientation in the sample, one can control the sample rigidity and thus can either suppress or promote the sample deformation.
Applicability of the Star Model on Indian Neighborhood: Case of Malviya Nagar, South Delhi
Authors: Kaur Simranpreet , Chhabra Pankaj
Published: April 2022

Over the years, there have been numerous debates and explanations on privatization of public space, its inclusivity, and of course the degree of publicness such spaces offer. The distinction of pure public space is a layered progression folding the publicness into a private space. The character sketch of these pseudo-public spaces have been defined by many theorists on the basis of accessibility, control, ownership, and typology transformation that happens. This paper bestows star model for measuring the publicness of such public spaces in a neighborhood, aiming to analyze the behavioral shift that subsequently emulates. The model is deliberated to be of value for analyzing the publicness of Indian neighborhoods in a rational manner with few implications of Indian context. The study concludes unravelling the new form of public space, supposedly taking control over our cities and its related complexities in redefining the meaning of publicness.
Sustainability & Comparative Impact Analysis of Coral Reef Bleaching in Indian Context
Authors: Goswami Mausumi , Ali Hussain
Published: April 2022

An estimated value of 500 million of the population are directly benefited through coral reefs related jobs, food and defence of coastal areas. Coral reefs help to reduce wave energy by 97%. They help to protect the coastal areas from storms, floods and wave energy by 97%. Natural disasters such as Tsunami and erosion of coastal areas are protected by reefs. In this process, they help to protect the lives of many staying in the coastal areas including animals, properties, and other natural resources. There are reasons for reef deterioration like change of climate, high pollution, destructive fishing, bleaching of coral reefs is a big concern now worldwide. Severe coral bleaching is also reported in India. A significant rise in the surface temperature of Sea has become a critical reason for coral bleaching. This work attempts to Study the link between sustainability , SDG goals of 2030 given by United Nations and coral bleaching. In this work study period is focused from 1985 to 2021 in the Indian coral reef bleaching areas.
A Study on How Indian Brands Connected with Customers During Coronavirus Lockdown in India
Authors: Sharma Monika , Thakur Sarima , Khurana Shopita
Published: April 2022

Every year, new companies and brands come into existence in India; and in this race standing a chance to be the best is endless. Hence to position itself to be the best, companies always aim at increasing their brand reach through various platforms. The most proven way to improvise the brand reach had always been through advertising. It had been evident that the most companies’ highly preferred mediums to advertise their products are television and the internet. In the past more than a decade the research reports have shown that the maximum number of viewership medium had been television and digital media. Keeping the desired results in consideration, most brands choose to spend millions on advertisements over these mediums. Even when the whole country came to a standstill due to the COVID pandemic, brands continued to advertise and promote their products. Some brands even changed their approach after considering COVID-19 and the lockdown, while others continued with their old advertisement sources and mediums. This study has analysed how brands in India have promoted their products on television and the social media platform such as Instagram, Facebook, and so on. The brands that have been selected in this study are Indian and international brands that have majority of their buyers in India.
Fabrication, Characterization, and Gas Sensing Properties of CaMnO3 Doped Polyaniline Nano Composite Thin Films
Authors: Reddy Ambresh , Patil Nirdosh , Bolegaon Neha N
Published: April 2022

Porous CaMnO3 doped polyaniline nano composite thin films were synthesized by the doping CaMnO3 by weight percentage (5%, 10%, 15%, 20%, and 25%) in aqueous solution of polyanline using chemical polymerization technique. The produced ﬁlms were characterized by X-ray diffraction (XRD), UV-Visible spectroscopy, Infrared spectroscopy (IR), scanning electron microscope (SEM), d.c electrical conductivity, and dielectric constant measurements. The optical properties of all investigated ﬁlms were studied, where the optical absorption of the prepared ﬁlms decreases with increasing the amount of CaMnO3 in both VIS (500–700 nm) and UV (200–400 nm) regions. The increase in conductivity with increase in concentration of CaMnO3 has been observed in CaMnO3 doped polyaniline composites. The H2S gas was used to study the gas sensing behavior of investigated films.
High-Temperature Impedance, Modulus Spectroscopy, and Conductivity Study of Nd Modified Barium Stannate Titanate Electroceramics
Authors: Kumari Manisha , Murikkoli Sarun
Published: April 2022

(Nd1−2x/3Bax)(Ti0.95Sn0.05)O3: NBTS electroceramics with different concentrations of Nd doping, i.e. x = 0.00 - 1.5 mol % are prepared. Structural characterization reveals the formation of single-phase tetragonal symmetry. Highly dense microstructures are observed in FE-SEM micrographs. Impedance, modulus, and conductivity studies are done at 350-500°C temperature. Negative temperature coefficient: NTC resistance nature is confirmed from the Nyquist analysis. Impedance spectra analysis reveals that grain resistance (Rg
) and grain boundary resistance (Rgb
) are dependent on temperature and Nd concentration in the NBTS ceramics. The frequency-dependent imaginary part of impedance (Z′′
) and electrical modulus (M′′
) reveal the localization of relaxation in NBTS ceramics at high temperatures. The activation energy obtained from the relaxation peak and the scaling formalism reveals that the conductivity is attributed to the oxygen ion vacancies. Conductivity study suggests the variation of frequency exponent, which follows correlated barrier hopping (CBH) model. These studies suggest that NBTS ceramics are potential candidates for future power electronics applications at high temperatures.
Chili Sauce Mix Incorporated with Mango Seed Starch, Its Application as Thickener and Stabilizer
Authors: N Sushma , Thomas Diya Anna , S Subhashini , Shankar Amar
Published: April 2022

India is one among the largest producers of mangoes. This research aimed to utilize agricultural waste from mango processing industries in which mango seed kernels are usually discarded. The seeds are rich in organic components and starch. The study broadly concentrated on the physicochemical, functional, morphological, and sensory properties of starch granule extracted from mango seeds and its application as a thickener and stabilizer in chili sauce in comparison to corn starch. Experimentation showed the total yield, swelling behavior, solubility, and water-binding capacity of the MSS to be in favor. The morphology and internal structures were characterized using Scanning Electron Microscopy and X-Ray Diffraction studies. The pH, titratable acidity, TSS, flow consistency, and serum separations were analyzed for chili sauce with mango seed starch. Mango seed starch is a potential source of starch in comparison to other conventional sources and its utilization at a large scale has chances to improve the economic viability of the mango processing industries.
Prototype for Automatic Fire Detection and Extinguishing Robot
Authors: Vemulapalli Harika , Gudavalli Madhavi , Azaharahmed Mohammed
Published: April 2022

Fire mishaps are common nowadays, and at times it has become very challenging for firefighters to save personage entities. It became hard for a human being too constant supervision during accidental fire situations. Consequently, in such cases, a firefighting robot is handpicked. Particular robots are most fruitful in industries where the odds of unintentional fires are severe. Moreover, the initiated vehicle can recognize the existence of fire and extinguish it involuntarily by pumping out water. Temperature sensors and smoke sensors are used for the detection of fire. It contains a motor-driver module that controls the gesture of the robot. A relay circuit is handed down to direct the pump, and it automatically sprinkles water when the fire is noticed. The proposed robot also has an LCD that displays the temperature, smoke, and fire rate.
Export Assistance Program and Handloom Industry: A Literature Review
Authors: Singh Vishal Kumar , Gautam Amit
Published: April 2022

This research focuses on the handloom industry's export support program. The present governmental export support program is divided into four determinants based on their features, and those four determinants of export help were found by a thorough literature research and analysis of the governmental aid programs for the handloom sector. The financial support structure has a significant impact on export assistance since it provides numerous tax refunds and other concessions. This research primarily focuses on diverse literatures relating to the handloom business, with the goal of extracting the common thread running across all of the studies.
An Innovative Method for Detection of Malicious Behaviours in Automated Vehicle System Using Hybrid Fuzzy C-Means Algorithm with Neural Network Algorithm Based Accuracy and Cost
Authors: P. Ananthi , V. Parthipan
Published: April 2022

Aim: To improve the predictive accuracy and cost analysis for malicious behaviors in automated vehicle systems using the Hybrid Fuzzy C-Means algorithm (HFCM) and Neural Network algorithm (NN). Materials and Methods: Accuracy is performed with two groups Fuzzy C-Means Algorithm and the Neural Network algorithm of sample size per group (N = 125). G power 80% threshold 0.05%, CI 95%. Mean and Standard deviation. Result: Independent sample T-Test was carried out using Fuzzy C-Means and Neural Network. C-means (92.1%) perform better than NN (89.6%). There is a statistically significant difference between Fuzzy C-means and with (p<0.01). Conclusion: The results conclude that the proposed Fuzzy C-Means algorithm helps to identify and detect with better accuracy and cost percentage at event systems.
Banknote Denomination Recognition on Mobile Devices
Authors: M C Sohan , A M Akanksh , M R Anala , R Hemavathy
Published: April 2022

Several mobile applications have been developed to facilitate denomination detection for blind users. However, none of the existing applications allow for detecting multiple notes in a single frame and relaying the total denomination, nor is there a dataset available for the new Indian currency notes, annotated for object detection training. We describe the development of a detection application that aims to improve on the previously existing solutions by enabling multi-note detection, continuous audio feedback, automatic torch usage, and minimal user-application interaction. YOLOv4 allowed the training of a lightweight and fast object detection model with high accuracy on a custom-created dataset post-demonetization of Indian currencies that is deployed on a mobile device.
Nano-Titania Supported Sulfonic Acid [Nano-TiO2-SO3H (n-TSA)] as Heterogeneous Solid Catalyst for Synthesis of Isoxazolyl-Thiazinones Under Solvent-Free Conditions
Authors: Dhawan Kapil , Singh Ruby
Published: April 2022

An efficient and solvent-free synthesis of new class of heterocyclic framework, i.e. 3-(5-methylisoxazol-3-yl)-2-subsituted-phenyl-1,3-thiazinan-4-one, has been carried out by the three-component reaction of substituted aldehydes, 3-amino-5-methyl-isoxazole, and 3-mercaptopropionic acid using titania-supported sulfonic acid (n-TSA) as a heterogeneous solid catalyst. Short reaction time with excellent yields, cost effective, easy workup process, and most important the recyclability of catalyst, is remarkable green reaction features of the present eco-friendly method.
Passive Filter Topologies for Grid Connected and Standalone PV Systems: A Survey
Authors: Jayaraman Meenakshi , VT Sreedevi
Published: April 2022

A passive filter is often necessary in grid connected and standalone distributed generation systems to reduce harmonics on the inverter output voltage/current waveforms. This article presents a survey of passive filter structures used along with voltage source inverters in grid connected and standalone systems. The paper brings in the salient features of existing passive filters throwing their merits and demerits. In literature, intensive work has been performed on the identification of new passive filter topologies with features including reduced elements, lower losses, and reduced harmonics. New filtering techniques based on the traditional schemes have also been proposed for easy control, less complexity, and reduced harmonic distortion. In this paper, a review of such newly developed filter topologies is carried out. This work would constitute a base for selection of a particular filter structure, which serves an essential component in standalone and grid connected applications.
Thermoelectric Properties of Pr3Se4 Compound: DFT Study
Authors: Alghamdi Ghadah , Kumar Ranjan
Published: April 2022

The electronic structure calculations for Pr3Se4 have been studied applying the density functional theory (DFT). Applying the semi-classical Boltzmann theory-based calculations, the thermoelectric properties have been calculated for undoped and optimized Pr3Se4 as a function of temperature. Due to the enhancements of power factor (PF) and electronic thermal conductivity (κe) for optimized Pr3Se4 compared to undoped compound, the electronic part of the figure of merit (ZTe) has improved. Calculations of thermoelectric properties indicate that the optimized Pr3Se4 can achieve a value of ZTe = 0.43 at 1,300 K.
Notions of Decomposition of β*
G -Continuity Via Grills
Authors: V Beulah
Published: April 2022

In this paper, we have introduced β*
G-local function as where the family of semi-preopen sets in the grill topological space (X,τ,G ). Also we have investigated the decomposition of β*
G-continuous map in the grill topological space. Furthermore, the weakly β*
G-continuous map is defined and examined.
Social Robots in Education for Long-Term Human-Robot Interaction : Socially Supportive Behaviour of Robotic Tutor for Creating Robo-Tangible Learning Environment in a Guided Discovery Learning Interaction
Authors: Alam Ashraf
Published: April 2022

The article discusses the possible applications of social robots in education, the technological and pedagogical challenges they possess, and the ways in which they may affect learning outcomes, concentrating only on robots intended to assist students in learning via social interaction. Author has highlighted three significant research problems : 1) Does robot tutors help improve students’ learning outcomes? 2) Does appearance and behaviour of robots have a significant role to play on academic engagement of learners? 3) What could be the potential roles of a robot in an educational setting? A statistical meta-analysis of previously published research articles is used to substantiate author’s claims. The larger aim of this article is to provide effective groundwork for future research by describing the expected outcomes of using social robots to offer education and identifying potential research areas for further inquiry.
Comparative Analysis of Customer Behaviour Using K-Means Algorithm Over Convolutional Neural Network with Increase Inaccuracy of Prediction
Authors: K. Sai Lekha , N Deluxni
Published: April 2022

To perform an efficient analysis of customer behaviour by comparing K-means and convolutional neural networks and improving the accuracy of prediction. Material and methods: The sample size for this project as 60 (Group 1=30, Group 2=30). For the customer segmentation behaviour it divides into groups with techniques like Manual, Semi-Automatic, and Automatic. In these techniques, the main problem is low accuracy value rate. To modify this, perform K-means algorithm technique. It allows the data to form a group for individual performance. Result: The data was analyzed to show the density and annual income with significant value (p=0.4512) and it gives the better performance with the validated effects of emotional display on the customers. So that we are able to get performance analysis from our customers and get better reviews. Conclusion: K-means clustering showed improvements in accuracy compared with convolutional neural networks.
Performance Management in Cloud Computing
Authors: Shyam Gopal , Ramamoorthy Shankar
Published: April 2022

Cloud service providers encounter a challenge in managing remote resources due to the dynamic nature of the cloud environment. The complexity of the process is increased by the requirement of maintaining service quality in line with customer expectations, as well as the extremely dynamic nature of cloud-hosted applications. As a result of developments in big data learning methodologies, traditional systems have given way to intricate systems. In the existing studies, it is shown that the resource adjustment decision-making process is intimately linked to the system's behavior, including resource utilization and application components. The most essential requirements and restrictions in cloud resource management, as well as workload and anomaly analysis approaches in the context of cloud performance management, are discussed in this paper. The related works are provided, with major methodologies in current studies ranging from data analysis to performance techniques. Finally, a list of open challenges is compiled, taking into account the identified gaps in the overall direction of the tasks under consideration.
Flexible, Stretchable Strain Sensor on PANI-CNT/PU Polymer Nanocomposite for Biomedical Applications
Authors: D B Niranjan , S Shibashish , Namboothiri Pramod K
Published: April 2022

The development of various flexible and stretchable materials has drawn in interest for promising applications in the biomedical field, such as health care monitoring, artificial intelligence, and wearable electronic skins. However, it’s still challenging to achieve tunable sensitivity and stretchable property based on particular application from large strain to small strain. Herein, we present interconnected nanocomposite PANI-CNT impregnated in polyurethane polymer. Filler materials PANI prepared by chemical oxidation method and CNTs are surface modified by acid oxidation method. Nanocomposite prepared by solvent-casting method using polyurethane polymer. Subsequent change of electrical behavior observed when concentration of PANI increased in nanocomposite. These prepared nanocomposites exhibit electrical conductivity and stretchability. Furthermore, nanocomposites are attached to the elbow and observe the change in bending movements of the elbow. Altogether, prepared PANI-CNT/PU nanocomposite can be assembled as e-skins for various purposes such as healthcare, human motion monitoring, and human-machine interface.
Synthesis and Photoluminescence Characterization of 3- MPA Capped CdZnTe Quantum Dots
Authors: JOHN U. Kiran , Mathew Siby
Published: April 2022

3-MPA capped CdZnTe alloy quantum dots synthesized using Na2TeO3 as the tellurium source under open atmosphere conditions in aqueous medium. The optical and photoluminescence properties of the CdZnTe quantum dots characterized using UV-Visible absorption and Photoluminescence spectrum. An excitonic peak at 527 nm observed in the absorption spectrum. Tauc relation and Urbach relation were employed to find the bandgap energy and urbach energy of the CdZnTe quantum dot. The quantum dot particle size was estimated using the bandgap energy from Tauc plot employing tight binding approximation, which was 4.75 nm. A high intense emission peak at 567 nm obtained in the photoluminescence spectrum. The emission peaks correspond to yellow fluorescence. The CIE chromaticity diagram gives color coordinate at (0.41,0.56) with a color purity of 92%. The high intense yellow fluorescent CdZnTe quantum can placed as potential candidates for fluorescent probes, biolabeling and cell imaging applications.
A Routing Algorithm with Sdn Controller Using Policy-Based Routing (PBR)
Authors: Kulkarni Raghavendra , Sharma Kalpana
Published: April 2022

Software defined networking (SDN) is a modern computer network architecture in which the control plane is separated from the data plane and applied centrally. SDN use in businesses necessitates the replacement of legacy network infrastructure, which comes at a high cost to the business. The phased rollout of SDN in the form of hybrid networks is the solution to this issue. Legacy devices' control planes must communicate with the SDN controller in hybrid networks. This connectivity facilitates the use of SDN in hybrid networks. Policy-based routing (PBR) is a mechanism in legacy networks that makes routing decisions based on policies set by network administrators and offers a versatile routing mechanism. Using an SDN controller and the Open Flow protocol, we presented a new approach for policy-based routing (PBR) in RIP-based hybrid networks in this article. The Open Flow switches send false metrics advertising packets to the legacy routers using this tool. We may alter the routing table of a legacy router using this procedure, which is dependent on the controller's policy.
Impact of Social Media Marketing on Organizational Performance: A Case Study of Amazon India
Authors: Kandi Venkata , Balakrishnan Sakthimala , G Sivakumar , N S Vijayalakshmi
Published: April 2022

With the intention of identifying how social media marketing can improve organizational performance, this research has focused on Amazon India. Through secondary data, different social media marketing strategies of Amazon are hereby identified at first. Then primary data is collected by sharing a survey questionnaire with one hundred random consumers of Amazon. From their responses, it was found that Amazon is using different tactics in different social media channels, such as following different topical festivals of India and creating emotional ads. These social media ads are helping the organization to engage with the consumers and draw them to their e-commerce site and almost ninety consumers stated that they buy something whenever they are re-directed to Amazon’s site through a social media ad.
A Study on Statistical Analysis of Risk Factors in the Assessment of Cardiovascular Events in Indian Population
Authors: Sudha S , Jayanthi K B , Abitha S B , Menagadevi M , Kavin Kumar K.
Published: April 2022

Cardiovascular disease (CVD) has emerged as one of the major health problem all over the world. In this study, statistical analysis is performed to identify the association of diabetes, cholesterol, hypertension, obesity, sex, and age with CVDs. A total of 710 patients are examined and their clinical parameters are collected. The datas are recorded and analyzed using R-studio. The analysis suggests that age, sex, hypertension, and diabetes are important risk factors for the occurrence of CVDs. The results of cases and controls are compared by chi-square test. Correlation of individual risk factor with carotid intima media thickness (CIMT) is done by Pearson’s correlation. Prediction of CVDs through measurement of CIMT from independent variables like risk factors is done using logistic regression model. The accuracy of the model is found to be 72.51%.
Impact of Transformational Leadership on Organizational Performance Through Employee Motivation
Authors: Tongkachok Korakod , Garg Shaifali , Balakrishnan Sakthimala , N S Vijayalakshmi
Published: April 2022

In order to find out how transformational leadership can increase organizational performance through employee motivation, this research focused on one of the well-renowned transformational leaders, Jeff Bezos. From secondary data, it was found that Jeff Bezos is responsible for implementation of several programs AWS Grow Our Own Talent, Surge2IT, UXDR Apprenticeship Program, and Amazon Technical Academy. These programs are the reasons that employees are motivated and are performing beyond expectation. From primary data it was found that employees love the way Jeff allows them to take part in decision making program and to follow innovation ways of working. After the financial performance of the organization for past 5 years was analyzed, only growth is found. It means these programs are motivating employees. Motivating employees are performing better and it is increasing organizational performance.
Congestion Management of GSTEB Routing Protocol Using K-Means Algorithm in Wireless Sensor Network
Authors: Arieth Madonna , Anuradha K. , Harika B. , Ali D.Nowshad , Chowdhury Subrata
Published: April 2022

A sensor node comprises of enormous nodes which can a variety of tasks such as recognize, indulgence, communication, and influence resource. Data transmission is the main aspect from starting to target. Once it is transferred between the node and within-cluster, the congestion will arise either node or in a resource allotment. So that it will affect the unremitting delay of reaching data, flow, the defeat of information to the destination, and the unfavorable use of a significant quantity of energy in the node. In this work, the impact of machine learning algorithms is studied using the GSTEB hierarchical protocol. By altering the type of input parameters, K-Means clustering on node energy usage can be performed. If congestion occurs, our proposal outlines a strategy for dealing with it and improving the CHPSCCC (Clustered Highly Prioritized Application-Specific Congestion Control Clustering Protocol) approach for congestion management. Simulation results show that in the proposed system there is significant growth of rises in the lifetime, energy, throughput, and packet loss.
Auditron: An IoT-Based Smart Audit System for Monitoring Electricity and Water Consumption
Authors: Satapathy Chirag , Gokhale Hrishikesh
Published: April 2022

In today’s scenario, water and electricity consumption are at an all-time high. We use these commodities on a daily basis but never bother to analyze and track their usage. The average electricity consumption of a household in Bangalore is around 300 kWh per month. The average water consumption is 150 liters per person every day. Considering a family of 3 people, this amounts to around 4,500 liters of water per person every month. These consumptions amounts are very concerning especially in an ever-growing city like Bangalore. Due to the growing population, the water demand has drastically increased. In order to regulate and manage the usage of these resources, we are proposing a simple device of an Audit System Internet of Things (IoT) Technology to help users manage and track their water and electricity usage with ease, thus saving the resources and their expenditure.
Sustainability Enhancement in Machining of DTC Titanium Alloy through Integrated Impact Assessment of Various Lubrication Strategies
Authors: Jadhav Prasad Anant , Ramachandran Deivanathan
Published: April 2022

Machining difficult-to-cut materials like Ti-6AL-4V is characterized by various negative environmental and social impacts, leaving a burden on the environment. Stringent ecological conditions imposed by the government made it necessary to develop a sustainable machining solution. The word "sustainability" refers to the unit process, which is long-term viable from an economic, environmental, social, and quality point of view. Furthermore, because production and operations managers need to know how the machining process contributes to Sustainability, the necessity to measure the Sustainability of machining activities has been recognized. As a result, this study presents a novel paradigm for evaluating the impact of various lubrication strategies on machining operations from an economic, environmental, and product perspective, which measures the Machining operation's Sustainability. The milling process is the focus of this study due to its frequent application in complex industrial jobs. The MQL milling with the lowest impact score of 27.6 is found sustainable.
To Develop and Implementation of Community Based Educational Intervention on Knowledge, Attitude, Stress and Coping Among Postmenopausal Women
Authors: Kaur Rajinder , Malhotra Reetu , Balasubramanian N
Published: April 2022

Menopause is a permanent halt of menstrual bleeding caused by the reduction of ovarian follicular activity in a woman's body.Perimenopause, or the transition to menopause, is a period of time that starts with irregular menstrual periods and concludes with prior menstruation Vasomotor symptoms, physical symptoms, psychological symptoms, and sexual symptoms.The aim of the study is to develop and implement Community Based Educational Intervention on Knowledge, Attitude, Stress and Coping among Postmenopausal women.Quantitative evaluation approach, true experimental research design of pre and post-testing with a control group will be for the present study. The target population of the present study will be postmenopausal women who met the inclusion criteria.In the proposed research investigator planned to develop community-based educational package on care of women after menopause. It is obvious that after menopause, women must face a great deal of stress because of physical, psychological, and emotional changes.
Design and Development of Decorrelation Stretch Technique for Enhancing the Quality of Satellite Images with Improved MSE and UIQI in Comparison with Wiener Filter
Authors: R Nanmaran , Priya S.Hari
Published: April 2022

Image enhancement is the process of increasing the quality of an image by enhancing certain features of an image and the resultant image is more suitable than the input image. This research is aimed at developing more efficient image enhancement techniques in the spatial domain. Materials and methods: Image enhancement using decorrelation stretch technique (N=30) is proposed in this work, and this method is compared with Wiener filter (N=30). The sample size used for both groups is 30. Results: The quality enhanced image is measured using Mean Square Error (MSE) and Universal Image Quality Index measure (UIQI). High UIQI and low MSE indicates the better enhanced image. The parameters of MSE (db) and UIQI are having higher values than the parameters of Wiener filter. The mean MSE value of decorrelation is 4.2715 db. Mean MSE of wiener filter is 32.0476 db. The mean UIQI value of decorrelation is 0.5640 db and that of Wiener filter is 0.5766 db. Conclusion: Image enhancement using decorrelation stretch technique is significantly performed better than Wiener filtering based on the experimental results and independent sample T test results using IBM-SPSS software.
Detection of Diabetic Retinopathy Using Convolutional Neural Networks
Authors: R Jaichandran , Sivasubramanian Vithiavathi , Prakash Jaya , M Varshni
Published: April 2022

In the modern world, diabetes is one of the major health problems that affects humans all around the world. Lack of early detection, prolonged diabetics, might lead to medical complications such as heart problems, eye vision problems, skin issues, etc. Diabetic retinopathy (DR) is a frequent abnormality of diabetics. To help patients with the early detection of diabetic retinopathy, in this paper, we propose a computer vision-based technique to analyze and predict diabetes from the retinal input images. Image preprocessing, segmentation, and feature extraction steps are applied. Convolutional neural networks (CNN) and Support Vector Machine (SVM) are trained with diabetic and non-diabetic retinal images. Results show CNN reports better accuracy in DR compared to SVM.
A Comprehensive Survey Using Novel Content-Based Filtering Technique to Improve Effectiveness on Social Media Datasets for Group Recommendation System Based on External Social Trust Networks
Authors: Vani Addagada , Ashok kumar S.
Published: April 2022

Aim:To build a Movie Recommendation system for Netflix to improve the accuracy percentage using Content-Based Filtering technique to analyze the prediction rate of movies. Materials and Methods: Two different algorithms are used Content-Based filtering algorithm and External Social Trust Networks to achieve maximum accuracy with a content based filtering with a sample size = 6 and external social trust network with a sample size= 6 was iterated 10 times for accurate outcome. Pre test is calculated by using G-Power tool value of 80% and confidence interval is 95% mean and standard deviation. Result and Discussions: These results proved that Recommendation System for Netflix using Novel Content-Based filtering algorithm gives better accuracy (0.94) in comparison with External Social Trust Networks(0.76). Conclusion: Content-Based Filtering algorithm helps to build a recommendation system gives effective results with the better accuracy rate of percentage.
Development of Fault Diagnostics and Prognosis System Based on Digital Twin and Blockchain
Authors: Jonne Gnagliga B. , Ibrahim Doucoure , Rai Laxmisha , Chen Qingguang , Liu Fasheng
Published: April 2022

In this paper, a development of fault diagnostics and prognosis system based on digital twin and blockchain is demonstrated. The main focus is to provide cheaper solution for maintenance operations, data safety, and machines’ life control. Initially, various details of prerequisites required by an engineer to conduct machinery condition monitoring is discussed. This include concepts of instrumentation, signal processing techniques such as vibration monitoring, motor volume signature analysis, and thermography where debris analysis and detection techniques are discussed. Furthermore, principles on how to operate maintenance operations in particular conditions illustrating the best techniques available for making a good maintenance decisions known as FEMCA (Failure Mode Effects and Criticality Analysis) are described. The experimental evaluation is performed to monitor the alignment of shaft and missing gear tooth using a simple locking mechanism using a sensor.
A Survey Paper on Automated Waste Segregator Based on Internet of Things Technology
Authors: S Bhuvaneswari , A Abirami , S Rithanya , RP Suvetha Sri
Published: April 2022

Municipal solid waste, commonly known as garbage, is a waste category comprising of items that are discarded. The waste that is involved is very flagrant, we approach a system called as Involuntary Solid Waste Segregator (ISWS), where the segregation of the waste like metal, glass and plastic, organic and sanitary napkins are carried out. To segregate the metallic waste, a magnetic field is generated with inductive sensor, for glass and plastic and organic waste used capacitive sensor, infrared sensors respectively. Once the waste segregated is amassed in a trash can and the amount is monitored in a server by Internet of things (IoT).
Genre of Song Identification Using Deep Learning
Authors: Dasari Kruthi , Hegde Nagaratna Parameshwar , Vikkurty Sireesha
Published: April 2022

Music genre identification is crucial for the classification and recommendation of songs in music applications. Manually labelling songs takes up a significant amount of time. In this paper, we propose a deep learning model to automate the process of genre identification. The process mainly involves three steps: preprocessing the dataset to get a simplified version of each song, building a deep neural network, and training and using it to predict the genre of songs. Input to the model is Mel-frequency Cepstral Coefficient (MFCC) values of the audio files from the GTZAN dataset that consists of 10 different genres. After training, the model produced a result of 60% accuracy. Observing the actual and predicted values, the model seemed to exhibit overfitting. To overcome this, we used dropouts and regularization in the model, followed by early stopping, which gave a final accuracy of 67.5%.
Facile Synthesis of Computationally Designed MgAl2O4/CeO2/Cu2o and MgAl2O4/CeO2/Ag2o Smart Heterojunction Photocatalysts for Aqueous Organic Pollutants Degradation
Authors: Hoque Khondaker Afrina , Kumer Ajoy , Chakma Unesco , Chowdury Al-Nakib
Published: April 2022

Two incredibly smart heterojunction photocatalysts MgAl2O4/CeO2/Cu2O and MgAl2O4/CeO2/Ag2O were designed from semiconductor components MgAl2O4, Ce2O, Cu2O, and Ag2O. All the component and heterojunctions were analyzed for electronic band structure and structural geometry through the GGA with PBE functional. The bandgap of 5.082 eV, 1.920 eV, 0.547 eV, and 0.00 eV were reported for semiconductor components MgAl2O4, Ce2O, Cu2O, and Ag2O respectively, whereas heterojunctions (MgAl2O4/CeO2/Cu2O and MgAl2O4/CeO2/Ag2O) surprisingly get converted into good conductors with a bandgap of 0.00 eV. The density of state and the partial density of state for all the component crystals and heterojunctions were also simulated, and make a comparative study. For further investigation of their nature, optical properties, such as optical reflectivity, absorption, refractive index, dielectric function, conductivity, and loss function, were determined, and proposed the mechanism of photocatalyst.
Implementation of Robotic Navigation Algorithms Using Partial Reconfiguration on Zynq SoC
Authors: Basha Mudasar , Siva Kumar M , Chinnaiah M C
Published: April 2022

The purpose for this research work is to design a heterogeneous method for adaptive, task-based computer hardware reconfiguration for adaptive mobile robotic applications. The proposed method uses the dynamic reconfiguration technique to modify the navigation system to meet the requirements of various navigation algorithms for accomplishing an assigned task. In this work, we have proposed an efficient architecture that satisfies the requirements with adequate hardware and software resources by dynamically reconfiguring the system. The ability to change resources allows robots to collaborate more easily, to enhance performance and fault tolerance. The method is endorsed with case studies in which a multiple mobile robots are loaded with bitfile and their behaviors are dynamically modified during runtime. This paper also proposes the hardware implementation of navigation algorithms on Zynq SoC, XC7Z020CLG484-1, using Xilinx Vivado 2017.3 to simulate and synthesize the design. Verilog is a real-time hardware description language, which is used to deploy multiple robots. Software Development Kit (SDK) is used to facilitate the generation of integrated software applications for Xilinx embedded processors. One of the important aspects of this work is adopting an FPGA-based robot in service-based applications for assisting humans in their daily lives.
The Impact of Internal Stakeholders on Building Sustainability
Authors: Olatayo Ayodeji Olusola , Adenuga Olumide Afolarin , Faremi Olajide Julius , Aderogba Aderemi M
Published: April 2022

Building collapses are becoming more common, resulting in the loss of lives, a waste of resources, time, and money. When a building collapses, the shock has a societal, and often even international impact, and causes disgrace to the entire chain of stakeholders in the building industry. This study identified the contributions of internal stakeholders on building collapse as well as identify the factors that influenced building collapse in Lagos State. A survey of one hundred and fifty (150) construction stakeholders was conducted with ninety-two (92) questionnaires successfully retrieved and processed for analysis. Random sampling technique was used. Data collected were analyzed using the frequency table, mean score, and ANOVA (Analysis of Variance). The result reveals that there is significant difference in the contributions of internal stakeholders on building collapse in Lagos State. The study concludes that all internal stakeholders have a significant role to play on building construction projects.
Knowledge, Prevalence, and Impact on Social Distancing on Coronavirus (COVID-19) Infection Spread in Young, Adult, and Aged Population: A Survey
Authors: A Akshaya , Ganesh Karthik , Dr Mohanraj
Published: April 2022

The spread of COVID-19 created unpredictable changes in both environmental and political norms. Social distancing is a technique to reduce crowd interactions to minimize the spread of disease within groups. A self-designed survey study was conducted among 100 individuals of the general population. The questionnaire was designed in the manner to assess their knowledge about COVID-19. The results and data from this study were analyzed using SPSS software. The findings are represented in pie charts. More than 95% of individuals were well aware of the disease nature of coronavirus. About 87% of participants felt that lockdown can be effective against novel coronavirus. 70% of individuals responded that developed countries are performing social distancing more effectively than developing and third world countries. Awareness and knowledge about coronavirus was found to be high. But due to negligence of people, COVID-19 is prevailing still as a pandemic. Further precautions and mitigation programs should be followed strictly by governments.
An Innovative Method to Enhance the Accuracy of Credit Card Fraud Detection Using Logistic Regression Algorithm by Comparing Random Forest Algorithm
Authors: Poojitha S. , Malathi K.
Published: April 2022

Aim: The objective is to develop a model to predict which transactions could be fraud with a high accuracy rate by using machine learning(ML) methods, such as the innovative Random Forest Algorithm. Materials and Methods: F1 score and accuracy rate are performed on fraud rates transactions in a dataset. The two groups (LR) the sample size is (N=20) and (RF) is (N=20) with G power value = 80. Results: To perform the transactions in the credit card by utilizing the card number, financial balance and client details, and if it is offline, the fraud has to steal the user's details in online transactions, which is not easily recognized by the client and bank authority, which prompts loss of sensitive data. (p<0.05) statistically significant value is compared to the amount and time since last purchase with a confidence level of 95% (=.519). (RF) algorithm is used for detecting credit card fraud. The accuracy is analyzed based on the dataset of 99.3%, where the (LR) has the accuracy of 99.1%. Conclusion: The performance of strategy is measured based on accuracy, F1 score, Precision, Recall. The results seem to be better accuracy for (RF) is 93.3%.
Comparing the Dementia Patient Monitoring Using Modern Algorithm Through Novel Deep Learning Technique and Transfer Learning
Authors: Prasanna N.P. , Jenila Rani D.
Published: April 2022

The main aim of this study is to monitor and detect the dementia patients using modern algorithms, deep learning technology, and comparing the accuracy rate between the deep learning algorithm and transfer learning. Materials and methods: Samples were collected, deep learning algorithm (N=20), transfer learning (N=20) in accordance to total sample size calculated using clinical.com. The accuracy rate of dementia patients was evaluated by using the novel Deep Learning Algorithm (DPLA) with the standard dataset. Results: Comparison of accuracy rate was done by independent sample T-test using SPSS software. There is a statistically insignificant difference (p>0.05). DPLA(80%) showed better results in comparison with transfer learning (40%). Conclusion: Novel deep learning algorithms appear to give better results than transfer learning to monitor and detect dementia patients.