bluuebunny/crossref_metadata_2025 huggingface dataset:
Design and Assessment of Electric Vehicle Performance Parameters based on Drive Cycle
Authors: Joseph Binsy , Bhoir Deepak Vishnu
Published: August 2021

Electric vehicle plays a significant role, in the future transportation across the world. EV has the potential to reduce air pollution and emission of Greenhouse gasses significantly compared to the existing fossil-fuel-based vehicles. Even though substantial progress can be expected in the area of embarked energy storage technologies, charging infrastructure, customer acceptance of Electric Vehicles is still limited due to the problems of Driving range anxiety and long battery charging time. We can solve most of these problems with the infrastructure development ,optimum sizing and design of the vehicle components and extensive study on vehicle dynamics under various real-time driving conditions. This research focuses on the Matlab software based co-simulation of Electric Vehicle system, including the battery pack and motor, to predict the vehicle performance parameters like driving range, efficiency, power requirement, and energy characteristics under different driving scenarios. The vehicle’s acceleration performance, energy consumption, and efficiency are determined by simulation and verified analytically. Using ADVISOR software the fuel economies and tail pipe emission for various vehicle models are determined by simulation and results are compared with Hybrid Electric vehicle models.
Chatbot for Mental Well-being
Authors: More Vivek , Koli Viren , Vijaykumar Vignesh , Jethani Vimla
Published: August 2021

With the world becoming more and more competitive every passing day, the number of people suffering from stress and other mental health issues is exponentially increasing. Even school children and senior citizens are becoming victims of stress and pressure in today's world. The mental health of an individual is as important as physical health is. But unfortunately, there is a lack of awareness and proper mental health facilities in today's society, which demands the individuals to fight against their odds without any support. Therefore, we propose a solution in the form of a chatbot that will act as a medium for the users to communicate with, let out their feelings and thus get relieved of the stress that is clogged up. A chatbot application will be available at all times at the user's expense and will also keep track of the user's mood over a span of time.
Text Summarization using Extractive and Abstractive Methods
Authors: Varade Saurabh , Sayyed Ejaaz , Nagtode Vaibhavi , Shinde Shilpa
Published: August 2021

Text Summarization is a process where a huge text file is converted into summarized version which will preserve the original meaning and context. The main aim of any text summarization is to provide a accurate and precise summary. One approach is to use a sentence ranking algorithm. This comes under extractive summarization. Here, a graph based ranking algorithm is used to rank the sentences in the text and then top k-scored sentences are included in the summary. The most widely used algorithm to decide the importance of any vertex in a graph based on the information retrieved from the graph is Graph Based Ranking Algorithm. TextRank is one of the most efficient ranking algorithms which is used for Web link analysis that is for measuring the importance of website pages. Another approach is abstractive summarization where a LSTM encoder decoder model is used along with attention mechanism which focuses on some important words from the input. Encoder encodes the input sequence and decoder along with attention mechanism gives the summary as the output.
Early Detection of Depression Indication from Social Media Analysis
Authors: Syed Maharukh , Narvekar Meera
Published: August 2021

Depression that stems through social media has been steadily growing since the past few years but with the current inclination towards social media reliance it is highly imperative to detect the early signs. Continuous observation of a user's social media interests and activities may highlight suspicious and negative thoughts. This observation can help in understanding their future course of action and also indicate any suicidal thoughts and behaviors. By using the machine learning models, early indications of depression detection can be addressed. This work studies different word embedding techniques for early detection of depression from social media posts. Further, this work develops a model using various NLP processes in order to address the issue of early detection. The recommendations can be useful as a Decision Support System for counselors, psychologist and also can be of good use by the cyber-crime cell department for criminal investigations.
Comparative Analysis of Deep Learning Techniques to detect Online Public Shaming
Authors: Surani Mehdi , Mangrulkar Ramchandra
Published: August 2021

Over the past years the exponential growth of social media usage has given the power to every individual to share their opinions freely. This has led to numerous threats allowing users to exploit their freedom of speech, thus spreading hateful comments, using abusive language, carrying out personal attacks, and sometimes even to the extent of cyberbullying. However, determining abusive content is not a difficult task and many social media platforms have solutions available already but at the same time, many are searching for more efficient ways and solutions to overcome this issue. Traditional models explore machine learning models to identify negative content posted on social media. Shaming categories are explored, and content is put in place according to the label. Such categorization is easy to detect as the contextual language used is direct. However, the use of irony to mock or convey contempt is also a part of public shaming and must be considered while categorizing the shaming labels. In this research paper, various shaming types, namely toxic, severe toxic, obscene, threat, insult, identity hate, and sarcasm are predicted using deep learning approaches like CNN and LSTM. These models have been studied along with traditional models to determine which model gives the most accurate results.
Pose Estimation and Correcting Exercise Posture
Authors: Kanase Rahul Ravikant , Kumavat Akash Narayan , Sinalkar Rohit Datta , Somani Sakshi
Published: August 2021

Our posture shows an impact on health both mentally and physically. Various methods have been proposed in order to detect different postures of a human being. Posture analysis also plays an essential role in the field of medicine such as finding out sleeping posture of a patient. Image processing based and sensor based approach are the leading posture analysis approaches. Sensor based approach is used by numerous models to focus on posture detection in which the person needs to wear some particular devices or sensors which is helpful in cases such as fall detection. Image processing based approach helps to analyze postures such as standing and sitting postures. Fitness exercises are exceptionally beneficial to individual health, but, they can also be ineffectual and quite possibly harmful if performed incorrectly. When someone does not use the proper posture, exercise mistakes occur. This proposed application utilizes pose estimation and detects the user’s exercise posture and provides detailed, customized recommendations on how the user can improve their posture. A pose estimator called OpenPose is used in this application. OpenPose is a pre trained model composed of a multi-stage CNN to detect a user’s posture. This application then evaluates the vector geometry of the pose through an exercise to provide helpful feedback. Pose estimation is a method in which spatial locations of key body joints is calculated using image or video of the person. This computer vision technique detects human posture in images or videos and shows the keypoints such as elbow or knee in the output image.
Implementation of Deep Learning Based Sentiment Classification and Product Aspect Analysis
Authors: Dhabekar Shweta , Patil M. D.
Published: August 2021

With the increase in E-Commerce businesses in the last decade,the sentiment analysis of product reviews has gained a lot of attention in linguistic research. In literature, the survey depicts the majority of the research done emphasizes on mere polarity identification of the reviews. The proposed system emphasized on classifying the sentiment polarity and the product aspect identification from the reviews. Proposed work experimented with traditional machine learning techniques as well as deep neural networks such as Convolutional Neural Network (CNN), Recurrent Neural Network (RNN) and Long Short Term Memory(LSTM) Networks. The proposed system gives a better understanding of these algorithms by comparing the outcomes. The Deep Learning approach in the proposed work successfully provides a mechanism which identifies the review polarity and intensity of the reviews and also analyses the short form words used by people in the reviews. The experimental results in this work, applied on amazon product dataset, shows that the LSTM model works the best for sentiment analysis and intensity of reviews with 93% accuracy. This research work also predicts polarity for short-form word reviews which is the common trend these days while writing the reviews.
Balanced : An Application To Improve Mental Health
Authors: Bhalerao Mrunal , Lewis Trisha , Salvi Raj , Kalantri Rakhi
Published: August 2021

Mental health reflects a person's emotional, psychological, and social well-being. A report by World Health Organization suggests that India is the most depressed country in the world. Hence, the idea is to develop an end-to-end solution for identifying and treating mentalhealth issues. This paper aims to develop an application to keep track of user's behaviour, both online and offline, to understand and identify the possible mental health issues using various analytical and psychological methodologies. The target users of this application would be the individuals just above the age of 18 which fall under the category of working class. Postidentification, the user is recommended a suitable change in his routine and behavior which would lead to a better lifestyle.Mental illnesses detection is a challenging undertaking because a misdiagnosis can lead to catastrophic consequences.Hence, our android application will take the necessary steps to accurately identify and treat the mental health issue.
An intelligent Crop Price Prediction using suitable Machine Learning Algorithm
Authors: Ghutake Ishita , Verma Ritesh , Chaudhari Rohit , Amarsinh Vidhate
Published: August 2021

Planning of crops for the next season has been a tedious task for the farmers as it is a difficult prediction about metrics of prices that their crop will fetch in a particular season which will be typically based on dynamic weather conditions. This leads to inaccurate prediction of crops’ prices by farmers, and they happen to wrongly select the crops or in haste they happen to sell their crops early without storing and thus earning less than what the same crop would have fetched them in the future. This problem could be addressed by an ML model which will predict the prices of crops in advance showing the proper analysis of the crop and presenting their future scenario so that farmers can select the right crops to strategize crop production which involves crop selection, time of sowing deciding crop pattern and storage of harvested crops providing enough insights for predicting the appropriate price in the markets.
Adaptive multi-layer structure with spatial-spectrum combination for hyperspectral image anomaly detection
Authors: Yan Hongmei , He Mingyi , Mei Hanxue
Published: August 2021

A new algorithm for hyperspectral image anomaly detection is proposed by designing an adaptive multi-layer structure with spatial-spectral combination information, which is different from the traditional anomaly detection algorithms only considering the spectral difference between the anomaly point and the background pixels, and ignoring the difference between the local spatial structure and spectrum. Firstly, the present algorithm not only calculates the spectral dimension difference between the pixels to be measured and the pixels in the background window, but also measures the spatial structure difference between the internal window and the background window. Mostly, an adaptive multi-layer structure for anomaly detection framework is carried out based on the idea of background suppression, and a multi-layered anomaly detector is constructed. The anomaly detection results of each layer of the detector are taken as the constraints, and the background information of the image input in the detector of the next layer is suppressed, adaptively suppressing the background noises. The experimental results show that the present algorithm makes better use of both the local spatial structure and the spectral dimension information than the traditional two-window models (global RX, local RX and KRX), adaptively suppresses background, reduces the false alarm rate, and improves the detection effect of the abnormal targets with fewer pixels.
Origine des inclusions dans les aciers peu alliés
Authors: Gatellier C. , Gaye H. , Lehmann J.
Published: August 2021

Dans cette synthèse bibliographique est donnée une description de la nature des principales inclusions susceptibles de se retrouver dans un échantillon d'acier au carbone brut de coulée.

Uévolution potentielle de la morphologie et de la composition de certaines inclusions à haute température et leur comportement rhéologique au cours du laminage à chaud de l'acier sont ensuite discutés.
Drawing places, recreating spaces: visual voices from at-risk children
Authors: Pinto Giuliana , Tosi Francesco , Incognito Oriana
Published: August 2021

Drawing is a highly participatory mode of communication, particularly suited to allowing children to express their knowledge and ideas about various aspects of reality. It is necessary to ascertain whether children are able to master drawing sufficiently to place it at the service of their representational intentions, and whether they possess the pictorial flexibility needed to articulate and differentiate their graphic representations. The presence and development of this important cognitive–symbolic ability are investigated. This exploratory study aimed to investigate, in children living in socioeconomic and cultural disadvantaged conditions, (1) the emergence and development of the pictorial flexibility needed to effectively represent and differentiate the building in which they live from the building in which they wish they lived; and (2) the patterns in the number and quality of pictorial differentiation strategies adopted for representational purposes. Two-hundred 8-to-12-year-old Brazilian children living in a favela were asked to produce two specific thematic drawings, representing their real house vs. their desired house. The children’s pictorial representations were coded according to their communicative efficacy (allowing the viewer to distinguish, in each pair of drawings, between the real house and the one desired by the drawer) and according to the number and type of pictorial strategies used to diversify the two types of buildings. The children were had sufficient representational flexibility to effectively perform a pictorial differentiation task, and express their point of view on the environment in which they live, and imagine alternative scenarios, adopting a variety of painting strategies. Drawing, prompted with a contrastive task, has proven to be effective in allowing even disadvantaged children to differentiate their real and desired urban environments. Children’s pictorial flexibility manifests itself through a wide range of strategies, varying in number and quality according to the age of the artists. As such, its use can be encouraged by educational interventions aimed at broadening the expressive potential of children, and as a tool for fostering resilience.
Impurity charge compensation in graphene by a polarized ferroelectric polymer and its effect on charge transport near the Dirac point
Authors: Figueroa Kelotchi S. , Zimbovskaya Natalya A. , Pinto Nicholas J. , Wen Chengyu , Johnson A. T. Charlie
Published: August 2021

Charge transport near the Dirac point (DP) was investigated in graphene using ferroelectric (FE) gating in the temperature range of 300 < T < 350 K. We observed that the conductivity (σ) near the DP had a positive temperature gradient that switched to a negative temperature gradient with increasing temperature. The switch to a negative temperature gradient shifted to higher temperatures and gradually weakened upon moving away from the DP. Impurity charge compensation via polarization of the FE together with a temperature-dependent graphene–impurity charge separation was proposed as being responsible for the non-monotonicity in σ(T). A self-consistent theory for graphene transport with impurity charge scattering and phonon scattering was used to analyze the results. Non-monotonic charge transport was also observed in the temperature dependence of the residual conductivity (σr). Theoretical analysis of both σ and σr revealed a temperature independent contribution of ∼1.16e2h that is probably inherent to pristine graphene.
Steiner Decomposition Number of Complete ռ —Sun graph
Authors: Ebin Raja Merly E. , Mahiba M.
Published: August 2021

If each subgraph of the decomposition π of the graph G has the Steiner number same as G then π is said to be a Steiner decomposition of G. The maximum cardinality among the Steiner decomposition π of G is the Steiner decomposition number of G and is denoted by π

st
(G). In this paper, we present the Steiner decomposition number for Complete n-Sun graph.
Prime Cordial Labeling of Some Graphs
Authors: Gayathri K. , Sasikala A. , Sekar C.
Published: August 2021

A bijectionfrom the vertex set V of a graph G to {1,2,…|V|} is called a prime cordial labeling of G if each edge uv is assigned the label 1 if gcd (f (u), f (v)) = 1 and 0 if gcd (f (u), f (v)) > 1, where the number of edges labeled with 0 and the number of edges labeled with 1 differ at most by one. In this paper we prove that 8-polygonal snake containing n number of 8-polygon, Splitting graph of Cn for n ≥ 5 and Armed Crown C2k Pm for all k ≥ 3 and m ≥ 2 admit prime cordial labeling.
Symmetric Prime and Symmetric Semiprime Ideals in Symmetric Semirgroups
Authors: Punitha Tharani A. , Uma Maheswari V.
Published: August 2021

In this note we introduce the notion of Symmetric Prime and Symmetric Semiprime ideals in Symmetric Semiroups and we define completely symmetric prime and completely symmetric semiprime ideals also we derive some results based on the above concepts.
Harary Index of Power 3 Mean Tree Graphs
Authors: Sreeji S. , Sandhya S.S.
Published: August 2021

The Harary index is defined as the sum of reciprocals of distances between all pairs of vertices of a connected graph G = (V, E). In this paper we introduce Harary Index of Power 3 Tree Mean graphs.
Ascending Bi-Pendant Domination Decomposition of Path and Cycle
Authors: Brishni V. , Maheswari V. , Bala Deepa Arasi K.
Published: August 2021

Let G = (V, E) be a simple connected graph. A pendant dominating set S of a graph G is a bi-pendant dominating set if V-S also contains pendant vertex. The least cardinality of the bi-pendant dominating set in G is called the bi-pendant domination number of G denoted by γ
b
p
e (G). If G
1, G
2, G
3, …, G

n
are connected edge disjoint sub graphs of G with E(G) = E(G
1) ∪ E(G
2) ∪ E(G
3) …∪ E(G

n
), then G
1, G
2, G
3, …, G

n
is said to be decomposition of G. In this paper, we define Ascending Bi-Pendant Domination Decomposition (ABPDD) and discuss the values of m in P

m
and C

m
which admits APBDD into n-parts.
Combining electrocardiogram signal with Accelerometer signals for Human Activity Recognition using Convolution neural network
Authors: Varshney Neeraj
Published: August 2021

As the environment getting polluted, people are suffering with different medical problems also people are causes about their health as well. Considering this in the mind, Body sensor based human activity recognition attracting researcher towards this direction. A fusion of electrocardiogram signals and accelerometer signals processed through convolution neural network is proposed in this paper. Accelerometer placed at different location of the human body are fused with the electrocardiogram signals, generated through the ECG sensors placed at the chest of the human body. These fused signal are processed through convolution neural network to automatically detect the features and finally apply softmax for classification of the activities. We choose mHEALTH dataset for the experiment and achieve 98.91% validation accuracy.
Connected Vertex-Edge Dominating Sets and Connected Vertex-Edge Domination Polynomials of Gem Graph Gn
Authors: Radhika V.S. , Vijayan A.
Published: August 2021

Let G be a simple connected graph of order n. Let D
c
ν
e (G, i) be the family of connected vertex-edge dominating sets of G with cardinality i. The polynomial D
c
ν
e (G, x) =

D

c
υ
e

(
G
x
)
=

∑

​

i
=
γ
c
υ
e

n

(
G
)

d

c
υ
e

(
G
i
)

x
i

is called the connected vertex-edge domination polynomial of G where d
c
ν
e (G, i) is the number of vertex edge dominating sets of G. In this paper, we study some properties of connected vertex-edge domination polynomials of the Gem graph G

n
. Also we obtain some properties of D
c
ν
e (G

n
, x) and their coefficients. Also, we find the recursive formula, to derive the connected vertex-edge dominating sets of the Gem graph G

n
.
Survey on Data Mining Techniques, Process and Algorithms
Authors: Nivethithaa K.K. , Vijayalakshmi S.
Published: August 2021

The term “Data Mining” is refers to the extraction of patterns and knowledge from large amounts of raw data and often defined as finding hidden information in a database. It insinuate analyzing data patterns in large volume of data using one or more software. Data mining involves effective data collection and warehousing as well as computer processing.
Machine Learning Design Thinking for Fluid Models
Authors: Priyadharshini P. , Divya P.
Published: August 2021

Machine learning and particularly algorithms based on artificial neural networks establishes a field of research lying at the intersection of different disciplines such as mathematics, statistics, computer science, and neuroscience. This approach is characterized by the utilization of algorithms to extract knowledge from large and heterogeneous data sets. A neural network technique is played to implement machine learning or to design intelligent machines for constructing mathematical models that can perform various complicated tasks. The set of machine learning algorithms have modernized and structured for fluid flows. It is helped to develop flow modeling and improvement techniques using neural networks the biologically impressed algorithms, current lines of mechanics research, and industrial applications.
Fuzzy Corner Metric Based Brain Tumor Segmentation and Grade Classification
Authors: Kalyana Sundaram M.S. , Krishna Veni K.S. , Gnanavadivel J.
Published: August 2021

The main idea of this work is to reduce the physician time by assessing with computer aided tumor detection Human investigation is the routine technique for brain MRI tumor detection and tumors classification. Interpretation of images is based on organized and explicit classification of brain MRI and also various techniques have been proposed. The proposed system segments the Brain MR images with the help of fuzzy corner points and the segmented tumor area is subjected for grade classification. Support vector machine classifier is implemented for the grade classification. The proposed system is addressing a simple and robust technique for the tumor diagnosis and also the performance is 89.5% which is comparatively high when compared to the traditional classification method.
Effective Utilization of Pineapple Waste
Authors: Madhumeena S. , Preetha R. , Prasad Sandip
Published: August 2021

India is the largest fruit and vegetable producer. Until fruit is eaten, fruit peel stays waste. Phenolic acids, ascorbic acid, β-carotenes, and flavonoids are the most bioactive components of pineapples. This is one of the secondary plant metabolites abundantly present in pineapple skins in this sample, ferulic acid. Ferulic acid is a low-toxic phenolic acid widely used in diet and cosmetics. Ferulic acid is extracted using different conventional and non-conventional methods such as Soxhlet extraction, Supercritical fluid extraction and Solvent extraction and the amount of ferulic acid is quantified using High performance liquid chromatography (HPLC). The study also evaluated the presence of total phenolic content (Gallic acid equivalent/GAE)and antioxidant activity. Soxhlet extraction using methanol and petroleum ether was the best solvent, methanol showed maximum ferulic acid concentration (0.7696 g/100g), phenolic content (2.365 mg g/GAE), antioxidant activity (45%) and percentage yield (90.5% mg). This study also analysed micronutrients such as vitamins (A, B, B1, B2, B6, B12 and C), calcium, potassium, phosphorus, iron, manganese, zinc and dietary fibre in the pineapple peel
Enzymatic Degradation of Polycarbonates: Response Surface Methodology (RSM) based approach.
Authors: G Sudha , V Ganesh
Published: August 2021

Polycarbonate is a tough polymer known for its extreme toughness, inertness and transparency and is considered to be chemically resistant. Polycarbonates are susceptible to photo degradation and thermal degradation. The mechanism followed in the degradation of similar polymeric compounds is found to be mostly hydrolysis reactions. Reactions of Bisphenol A polycarbonate with the lipase Candida rugosa were carried out over a period of 72 hours at different temperatures ranging from 25 oC to 65 oC and at different lipase activities of 400 U/ml, 800 U/ml, 1200 U/ml and 1600 U/ml. The weight loss of polycarbonate was studied against various factors. It is found that there is a rapid loss of polycarbonate around the time period above 48 hrs and at the temperature 55 oC for above enzyme activities. The supernatant was subjected to FTIR and the presence of the Bisphenol A, a monomer was found. The results were subjected to the statistical tool, Design of Experiments, in which the fitness of the results were statistically analyzed and the interactions between the parameters studied. The Response surface methodology (RSM) and the ANOVA analysis were performed on the experimental data and the parameters were found to be non interactive. The model equation for the degradation kinetics is obtained from the coefficients of the ANOVA analysis and the fitness of the model data with the actual obtained experimental data is found to be close and similar over the parameters
Process design scheme on the feasibility of 1-decanol as a solvent in liquid-liquid extraction to recover anhydrous citric acid from water
Authors: Krishnan Suresh , Kapoor Ashish , Venkatesan D. , Sofiya K. , Balasubramanian S.
Published: August 2021

In this present study, we developed a theoretical process design scheme (PDS) to check the feasibility of solvent 1-decanol to recover citric acid from water by liquid-liquid extraction followed by series of unit operations such as vacuum evaporator, crystallizer, and filter using ASPEN PLUS TM. Literature suggested that the 1- decanol can serve as a solvent to recover the citric acid from water. However, the conditions maintain for the maximum production of anhydrous citric acid have been reported under the equilibrium condition. We incorporated the binary interaction parameters of the NRTL model in the simulation, as reported in the literature. The separation factor obtained from the simulation is compared and validated with the published literature data under a room temperature (25◸C). We performed the mass balance and sensitivity analysis for the developed PDS. The results show that the maximum quantity of anhydrous citric acid is obtained in the extract phase when the solvent to feed ratio is more than six.
Design and Implementation of 7 Stage Bandstop Filter for Wireless Modem
Authors: Aarthy S.T. , Kolangiammal S. , Ukendran G
Published: August 2021

In modern wireless communication, microwave system performance can be degraded because interference can occur due to the signals from other existing wireless communication networks. The 802.11a WLAN in-band signal, which occupies the 5-6 GHz range and 802.11b WLAN system signals covering the 2.4-2.48 GHz frequency band, is currently the main interference.
Artificial Neural Network Model for Predicting Fraudulent Attacks
Authors: Archana P , Divyabharathi P , Camry Joshya Y , Sudha
Published: August 2021

Now a days Artificial Intelligence is an emerging technology. Neural network concepts used in many applications at present situation. The usage of internet increases day by day as well as the lack of security increases day by day. Mainly phishing scams emerges highly in case of network security. In this paper Neural network concepts, how to train and test the data using Artificial neural network has been discussed which gives an brief idea about usage of Neural net concepts in field of Network security. The properties such as feed forward back propagation network form, gradient descent momentum training purpose, sigmoid transfer function, supervised learning model used to train the model for predicting fraudulent attacks.
Authentication and Identity Validation Blockchain Application
Authors: Arun N , Mathiyalagan R , Suchithra
Published: August 2021

The biggest obstacle to electronic migrations of many systems is the need to protect the details and to check the identity of users. Currently, the use of dual-factor authentication is based occasionally on a password. The problem with these approaches is that passwords are extremely insecure and authentication by two factors usually involves the sending of code via SMS or a third-party provider. The blockchain might be a solution to this problem. A 50 billion dollar currency is managed by blockchain. But authentication could be subject to the same cryptographic principles. Thus, blockchain authentication eliminates someone from maliciously modifying the ledger when they distribute a ledger to all network members. A majority of the network shall check its validity any time a block of data is attached to a chain. That guarantees the completeness of the ledger. You can then make sure to send passwords safely using public-key encryption, such as highly protected RSA encryption. The receiver could then search for an entry in the unchanged blockchain, which would result in a remarkably safe and reliable way of handling identity verification. These rules apply for the transformation into a stable, fast, reliable, and readily available service from the election process, state identifiers to dual-factor authentication.
A Study On Finding The Most Prevalent Age Groups Of Diabetic Retinopathy Among Diabetic Population Using Fuzzy Matrix Theory
Authors: Subhramaniyan T. , Suruthi S. , Paulraj M.S. , Ragunathan M. G. , Jayanthi J.
Published: August 2021

In this paper, authors identified the age group of Diabetic population which is affected by Diabetic Retinopathy (DR) using Fuzzy Matrix Theory. It has been shown that there is no significant difference between the men and women age group among Diabetic population developing DR.
Renewable Energy Sources: A Review
Authors: Neha  , Joon Rambeer
Published: August 2021

As a result of the rising everyday energy demand of the entire world population, the earth becomes an increasingly global village, while the earth cannot swing its form. For meeting human communal as well as economic development, education as well as health, drive and its related assets are increasingly needed. The return to sustainability to help fight temperature change is an ideal way to meet potential energy demand. The study looked at prospects related to renewables such as energy security, access to energy, social as well as economic development, and temperature change mitigation and environmental and health issues reduction. Given such benefits, the growth of clean energy sources is hindered by obstacles to climate change mitigation. This include market failures, lack of awareness, access to raw materials for future use of clean energy and our daily carbon footprint. The report has recommended a number of measures and policy recommendations to help meet the goal of carbon reduction, climate change mitigation and the safeguarding of a clean atmosphere and affordable resources for future generations.
Arduino Controller Based 3-Switch Isolated DC-DC Boost Converter for PV and Battery Application
Authors: William Christopher I. , Jones Priya J. , Raghul Axin X , Vignesh Kumar P. , Vimal Raj S.
Published: August 2021

This paper discusses a Arduino controlled 3-switch Isolated DC-DC Boost converter for PV and battery application. The presented converter has vital benefits such as a switch reduction, snubber circuit elimination with an additional diode, a capacitor; obtain the same primary and secondary voltage waveforms of the transformer with duty cycle variation. The MATLAB Simulink model of the presented converter for 95W PV system has been developed for 20V dc input. The hypothetical forecasts and the performance of the PV based presented converter has been effectively confirmed with the aid of simulation results. The experimental setup of the presented converter for 100W PV module has been successfully implemented using Arduino Uno microcontroller to confirm the simulation outcomes.
Numerical Modeling of Flow through the Vertical Rectangular Microchannel for Drug Screening Applications
Authors: Seelam Kalpana , Daisy Rani A.
Published: August 2021

A numerical study of flow in the rectangular vertical microchannel for drug screening applications is described. The flow characteristics through the microchannel are presented by incompressible Naiver-Stroke equations. Flow rate is evaluated from numerical modeling to simulate the drug flow through the microchannel. Here in this study, computational fluid dynamics based finite element method commercial software COMSOL is used for simulation of drug flow through the artery for cancer drug screening applications. The simulation work also presents the diffusion velocity at the intersection area between the drug and cancer cells..
Load Allocation as Quality and secured in Mobile Cloud Networking Location
Authors: Elizabeth Rani G. , Ajay Sukumar G. V. , Umesh Chandra T. , Anki Reddy K. , Sakthimohan M.
Published: August 2021

In portable cloud organizations (MCNs), a versatile client is associated with a cloud worker through an organization entryway, which is answerable for giving the necessary nature of-administration (QoS) to the clients. On the off chance that a client expands its administration interest, the associating passage may neglect to give the mentioned QoS because of the over-burden interest, while different entryways remain underloaded. Because of the expansion in burden in one Gateway, the sharing of burden among all the passages is one of the imminent answers for giving QoS-ensured administrations to the portable clients. Moreover, if a client makes trouble, the circumstance turns out to be all the more testing. In this paper, we address the issue of QoS-ensured made sure about help provisioning in MCNs. We plan a utility boost issue for quality-guaranteed made sure about burden sharing (QuaLShare) in MCN, and decide its ideal arrangement utilizing sell off hypothesis. In QuaLShare, the over-burden passage identifies the getting out of hand Gateways, and, at that point, keeps them from partaking in the closeout cycle. Hypothetically, we portray both the issue and the arrangement approaches in a MCN climate. At last, we explore the presence of Nash Equilibrium of the proposed plot. We expand the answer for the instance of different clients, trailed by hypothetical examination. Mathematical investigation sets up the accuracy of the proposed calculations.
Prediction of GPS TEC during the X9.3 Solar Flare for DGAR low latitude station by using OKSM
Authors: Kiruthiga S , Mythili S , Mukesh R , Karthikeyan V , Vijay M
Published: August 2021

The effect of solar flares on the ionospheric regions of earth, which in turn affects signals of the various Global Navigation Satellite Systems, is a very important criterion to be considered in satellite communication. In this paper, we are investigating the prediction capability of the Kriging based Model and its effect on calculating the signal delay of GPS system on 6.9.2017during which NASA have observed a solar flare which have recorded X9.3 on solar storm scale. The GPS data used in this paper for prediction of TEC is taken from the DGAR Island station. The Vertical Total Electron Content data for GPS is predicted from 3rd September 2017 to 7th September 2017 by using the previous collected 6 days of TEC data of the low latitude DGAR station from IONOLAB and also by using the input parameters like Kp index, SSN, Ap index and Dst index. The predicted results are validated by comparing them with IRI 2016 and IRI PLAS 2017 model collected during the same dates.
IoT Based Energy System in A Facts of Principle Intrusion on Power Administration
Authors: Rajasekaran M , Srinithi R , Sanjana S , Saadurya K V
Published: August 2021

The Stimulation to accomplish energy usage at a residential direct Asian country is influenced by political economy, status, and technical reasons. Economically, it offers a discount of state subsidies and electricity bills. The ecological condition facet permits the reduction of CO2 level. we are able to limit the availability to the house by pre-default setting the worth to be consumed so energy will be managed by limiting. the facility administration system comprises of Alphanumeric Power cadences are put in apiece shopper unit and an Electricity e-Billing scheme at the energy supplier aspect. Wireless sensing element network sends its power usage reading exploitation data back to the energy supplier wirelessly. On the facility supplier aspect, they’ll amendment the devices’ priority once power is distributed within the low vary.
An Enhanced Fuel Consumption Machine Learning Model Used in Vehicles
Authors: Dhanalaxmi B. , Varsha M. , Roshan Chowdary K. , Mokshitha P.
Published: August 2021

In the present world, some of the people are not able to pay expenses for petrol/diesel. The model which we are generating will be useful for many people. The system which we are generating is a data summary approach will be based on distance rather than traditional conventional time period when developing personalized machine learning model for fuel consumption. This system is utilized within conjunction with vehicle pace Also seven predictors inferred starting with way review to prepare a neural system model utilizing machine Taking in that predicts Normal fuel utilization done vehicles. The proposed model can be easily developed for each individual vehicle and fitted into one fleet to optimize fuel consumption over entire fleet. The model’s predictors are comprehensive on fixed window sizes and on the distance travelled. Different window sizes are evaluated and the results mean that the 1km window can estimate the fuel consumption with a coefficient of 0.91 and it also means less than 4% peak to peak percentage error for routes that include both city and highway duty cycling sections.
Electric vehicle routing problem optimal solution
Authors: Mesa F , González Granada J R , Correa Velez G
Published: August 2021

The large distribution companies of goods have the challenge of solving the problem of offering an optimal service in which different interests are faced which determine the decisions of the company, the problem is reduced to providing the best customer assistance, with low restrictions. operating cost on a route. Due to this, we see the need to make the programming of the routes of each vehicle as equitable as possible in terms of the capacity of the vehicle and the available fuel, in addition, it seeks to reduce the distances in which the vehicle travels without load. In this article we will demonstrate in detail in a document the optimal solution to the electric vehicle routing problem, which consists of determining optimal routes for a transport company to make efficient use of available resources, saving electricity and time, among other variables. Initially, the basic concepts about the operation of electric vehicles are described, later the concepts and modalities of vehicle routing are discussed, among which are the problem of routing open vehicles and the problem of routing vehicles with backhauls, later the scenario to develop the respective routes. and show the results with the optimal routes and routes, finally the conclusions obtained from the development of the techniques are exposed.
Active learning and knowledge in physics: a reading from classroom work
Authors: Prada Nuñez R , Hernández C A , Gamboa A A
Published: August 2021

This research article shows the findings of a study that sought to demonstrate the results of a methodological intervention implemented in classes of an eleventh-grade course in the area of Physics, in a public school in the city of San José de Cúcuta, Colombia. The intervention consisted of applying some active learning strategies accompanied by methodological tools such as collaborative work in order to measure the impact of the intervention on the level of disciplinary knowledge of students with a pre-test and post-test. The results show a significant increase with a value of 0.49 at the end of the intervention, which suggests that the subjects participating in the study improved their level of conceptual appropriation in physics after the application of active learning strategies.
Construction of an amusement park using STEAM and LEGO education to participate in the science fair
Authors: Rico-Bautista N A , Rico-Bautista D W , Arévalo-Pérez N
Published: August 2021

This article explains details of the participation in the Science Fair that took place in the 2019 school year by some seventh-grade students from “Colegio Isidro Caballero Delgado”, Floridablanca, Colombia. This event is a space established by the institution, which takes place once a year to show different projects and experiments carried out by students from each of the school grades. The seventh-grade students for their participation took as their theme an Amusement Park; with this theme, they built different prototypes that resemble mechanical attractions using LEGO Education cards and applying STEAM. The aim is to explain different themes seen in the mathematics course during the year playfully and amusingly to the participating public through the operation of each of these prototypes and physics topics in its structure or operation. The structure of the document contains a first section, the introduction in which the context of the educational institution, the development of the science fair, and the use of LEGO Education cards for the 2019 version are addressed; a section II where the methodology and the applied strategy are detailed; in section III the results obtained are mentioned, and finally, in section IV the conclusions and possible recommendations are presented.
Energy Efficient Buildings with Algae
Authors: Yaman Y , Tokuç A , Sener I , Altunacar N , Köktürk G , Deniz I , Ezan M A
Published: August 2021

The biggest part of the energy consumption of buildings is for thermal comfort. Awareness on climate change and concerns about the depletion of natural resources made the necessity to use renewable energy sources in buildings evident. In this context, microalgae have high surface efficiency and consume inorganic carbon, thus enabling carbon-neutral operation. They can be integrated into building façades with photobioreactors to reduce energy demands. This paper aims to clarify and discuss the role of microalgal technologies in energy-efficient architecture. The thermal performance and energy generation properties of microalgae façades are comprehensively reviewed. The results show that microalgae provide dynamic shading and thermal insulation, thus have the potential to significantly reduce the thermal load and energy demands of buildings and increase the building performance. Consequently, besides the thermal performance of microalgae façades, evaluation of daylight, lighting, environmental and cost performance, technical applicability and aesthetics are necessary.
An Empirical Case on the Measurement of China’s regional Low-carbon Development Level
Authors: Ye Meng , Zhang Ruichao
Published: August 2021

The ecological problems brought by the rapid development of the economy and society have threatened humanity’s sustainable development. As the world’s largest carbon emitter, China is still at a critical stage of industrialization, and it is urgent to solve the problem of how to realize the low-carbon circular development of the economy. This paper constructed the evaluation index system of regional low carbon development from the three dimensions of development, low carbon, and ecology. Based on the entropy weight-TOPSIS model, the index was quantitatively analyzed with the data of 30 provinces in China in 2018. According to the measurement results, 30 provinces, were clustered into low-carbon development zones, relatively low-carbon development zones, relatively high-carbon development zones, and high-carbon development zones according to the low-carbon ecological development level. The results show that China’s overall low-carbon economic development level is not high in 2018, with the south being superior to the north, and the eastern coastal areas of Guangdong, Jiangsu, Shandong, and Zhejiang being significantly prime to other regions. Finally, suggestions are given for different types of low-carbon development areas.
Flush Intensity of Mango (Mangifera indica L. c.v. Carabao mango) Leaves as Affected by Different Flush Induction Protocol
Authors: Ventura C E , Paguia H M , Paguia R Q , Telmo R B , Marabe E G
Published: August 2021

The study was carried out to validate the effect of different flush induction protocol on carabao mango which was conducted in Alion, Mariveles, Bataan, Philippines with the following treatments: no intervention (T1), pruning only (T2), pruning with urea applied in soil (T3), pruning with urea spray (T4), pruning with irrigation (T5), and complete flush induction protocol (T6). Results revealed that providing water hasten the flush induction of mango. The complete flush induction protocol (T6) significantly had the highest flushing percentage and the longest flushing duration. In terms of leaf produced per flush, pruning alone (T2) and pruning with urea spray (T4) equally produced the highest number of leaves per flush having 16 leaves. On the other hand, different flush induction protocols have no direct effect on flush and stem length, stem diameter, flush dry weight, and in the amount of nutrients in the flushes except for total amount of iron.