bluuebunny/crossref_metadata_2025 huggingface dataset:
The First International Conference on Advances in Computational Science and Engineering (ICACSE 2020)
Authors: Loganathan K , Mohanraj M , Sakthivel P , Sivakumar M
Published: July 2021

The First International Conference on Advances in Computational Science and Engineering (ICACSE 2020) on December 25 & 26th, 2020 which is planned to be held at Coimbatore, India. As the covid-19 pandemic spreads endless, according to the direction received from the government and suggestions received from some participants, the organizing committee decided to convert ICACSE 2020 into a fully virtual mode conference. ICACSE 2020 conference was organized by the Live4Research Institute of Research and Development, India. The main objective of the conference is to provide a platform for researchers, professors, and engineers to share their contributions to recent trends and developments in Engineering and Sciences. The scientific event brings together more than 300 researchers. Initially, the conference structure was divided into oral presentations and keynote speeches. In the oral presentations, some scholars' papers were selected as excellent papers, were given about 5-10 minutes to present their oral presentations one by one. Then the keynote speakers were each allocated 30-45 minutes for their plenary talks. We have received tremendous response from all over India and overseas (Malaysia, Oman, Ethiopia, Peru, Columbia, USA).

Through a rigorous peer-review process, all submissions were performed double blind review to check their quality of content, level of innovation, significance, originality, and readability. Based on the expertise review comments, only 295 papers were accepted, and the corresponding authors were invited to submit their papers for final publication. The accepted papers are published by IOP Conference Series “Journal of Physics: Conference Series (JPCS)”. The conference proceeding is a compilation of the accepted papers and represents an interesting outcome of the conference. This proceeding covers six chapters:

1. Advances in Computational Mathematical Sciences

2. Advances in Computational Physics and Material Sciences

3. Advances in Computer Science Engineering

4. Advances in Computational Electrical Engineering

5. Advances in Computational Electronics and Communication Engineering

6. Advances in Computational Civil Engineering

we would like to thank the keynote speakers, authors, and listeners for their excellent contributions. We wish to extend our sincere gratitude to the organizing committee, reviewers, and volunteers for their constant support. We greatly acknowledge our technical partner Cloudin Software Tech Labs Pvt. Ltd, Coimbatore, India for their effort in publicity and promotion of the conference. We greatly acknowledge all of those who supported ICACSE 2020. The support and contribution of each individual and institution were the backbones of the conference. In specific, we would like to extend our privilege to thank the organizing committee for its valuable inputs in steering the conference program to attain a grand success and reviewing the submitted papers.

List of COMMITTEE and logos are available in this pdf.
GMJ Coding Using Even Felicitous Labeling and Bistar Graphs
Authors: Manshath A , Hariprabakaran P , Maheshwari V , Balaji V
Published: July 2021

In this paper,using GMJ(Graph Message Jumbled) code, we developed a technique for coding a confidential message by applying the even felicitous labeling to the bistar graph Bv>0j.We presented two illustrations for transfering plain text into cipher text(picture coding), method for labeling an even felicitous graph and flowchart is outlined.
Effect of Non-linear Radiation on MHD Mixed Convection Flow of a Micropolar fluid Over an Unsteady Stretching Sheet
Authors: Kataria Hari , Mistry Mital
Published: July 2021

The current analysis explores the results of non-linear radiation on an unsteady stretching mixed Micropolar fluid. Issue modelling leads to a framework of PDE, reworked by transformations into non-linear ODEs. The Homotopy analysis methodology is applied to resolve the matter. The diagrams address the impact of the Magnetic parameter, unsteadiness parameter, Eckert number, Micropolar parameters, buoyancy parameters, Radiation parameter, Temperature ratio and Schmidt number on velocity, temperature, and concentration gradients. Amount of Nusselt number will increase in massive Prandtl number values, within the case of the high values of the unsteadiness parameter skin friction, wall couple stress and Sherwood decrease.
Distributed filtering stochastic parameter learning algorithm for discrete-time random nonlinear systems with delay
Authors: Francis Raj L , Dorathy Prema Kavitha D
Published: July 2021

Distributed filtering algorithm for a discrete time random nonlinear stochastic systems associated with state delay for the distributed wireless communication sensors are discussed in this paper. Stochastic Parameter Learning Algorithm (SPLA) is tend to aim at obtaining a collection of stochastic filter parameters in a finite limited time horizon, that minimize the traces of the upper limits which is permitted to reduce the error variance matrices of the concerned stochastic filter system’s states and delay measurements. Filter gain values of the filter derived by the determination of Riccati type difference equations, estimates systems states with delay. Two different filter rules are taken into account for the SPLA discrete time random nonlinear systems with steady state space equations model. Zero mean distinct covariance matrix along with the constructive state values and constant time delay are focused in compatible dimensions. The variance of the projected systems predicted noise and the actual estimated noise are validated through numerical examples.
Euler’s computational approach for damped oscillatory solutions of RLC circuits
Authors: Malarvizhi M , Karunanithi S
Published: July 2021

In this paper novel techniques for nonlinear frequency domain region problems with respect to linearity are examined. A notable methodology called as Modified Euler’s method and improved Euler’s method to perform nonlinear recurrence domain investigations of RLC circuit problems. Here a combination of waves approximates the driving forces to attain its damped oscillatory solutions. The two different cases were analyzed as, stability of the RLC circuit when the applied voltage is equal to zero and the forced oscillations of the RLC circuit when the applied voltage is equal to ?0?????. To keen the strength of investigation, stability analysis and non-oscillatory behavior of the RLC circuit are explained along with periodical time.
AMGL Coding Techniques With Skolem Mean Like Labeling and Two Star Graphs
Authors: Shendra Shainy V. , Hariprabakaran P. , Swathy V. , Balaji V.
Published: July 2021

In this paper, we have found a technique for coding a secret messages by applying the skolem mean like labeling on the two star graph K
1,φ Λ K
1,π for two different cases π = φ+1 and π = φ+4 using AMGL (Alphabets maneuvered Graph Labeling) code. We provided two illustrations for converting plain text into cipher text (picture coding) and method for labeling the skolem mean like graph is described.
Euler-Painleve transcendents, exact solutions of nonlinear PDE
Authors: Sivagami G , Selvi R K , Padmasekaran S
Published: July 2021

In this paper, some invariant reductions and exact soluions are obtained for a nonlinear partial differential equation by Clarkson Kruskal method. The reduced ordinary differential equation is shown to convertible to Euler-Painlevé transcendents.
Coding Technique With Two and Three Stars, SSML(N4,L2) and GMJ CODE
Authors: Uma Maheswari G , Hariprabakaran P , Balaji V
Published: July 2021

In this paper, we introduce a coding technique for converting a text message using sub super mean labeling on two and three star graphs to a picture coding message. The first part of this paper there are some definitions and discussions for the existence graph and in the second part there are some illustrations to explain how the text message is converted in to picture code, by using graph labeling, and it maintain secrecy, possess intricacy and provide a sense of sufficiency. Secrecy is the practice of hiding information from certain individuals or groups who do not have the need to know, perhaps while sharing it with other individuals that which is kept hidden is known as secret.
A Two Stage Queuing System with delay time
Authors: Shyamala S. , Suresh K. , Anantha Lakshmi S.R.
Published: July 2021

This paper discusses about a two stage queueing system with shared server and the delay time between two end to end responses. This system is examined as almost the process of quasi-birth and death and the necessary and sufficient conditions for system stability are discussed. The ErntPS algorithm for VoIP Services has recently been investigated for average delay in queueing and it has been proven that ErtPS can allow more users than UGS. However, we need the distribution of probabilities of queue delays in order to include information necessary for QoS rather than the average queue delays. Some fascinating performance measures are achieved by matrix geometric method. The server wishes to determine the optimal point of differentiation and its optimal buffer size. Finally we find the delay time differentiation and the specific probabilistic system descriptors.
Synthesis of ferrites using various parts of plants: a mini review
Authors: Kalia Shyam , Kumar Abhishek , Munjal Neha , Prasad Nupur
Published: July 2021

Ferrite nanoparticles are magnetic. They also show photocatalytic and antibacterial activities. These unique properties make them extremely useful for various applications e.g., they can potentially be used for electronic equipment, telecommunication systems, radar, sensing material, catalytic and photocatalytic applications, and several biomedical applications. Several methods have been developed to synthesise these materials. These include sol-gel, co-precipitation, ball-milling, combustion, hydrothermal heating, and microwave hydrothermal procedure. Recently, these materials have been using various parts of plants. Hibiscus rosa-sinensis, Hydrangea paniculata, rosemary, nyctanthes arbor-tristis, sesame seed, aegle marmelos, Limonia acidissima juice, aloe vera, amaranthus blitum, ginger and cardamom, were used for this purpose. Ferrites of silver, cobalt, zinc, and nickel were prepared successfully. Few doped ferrites, e.g., silver doped cobalt ferrite, nickel doped zinc ferrite, and zinc doped nickel ferrite were also synthesised. Use of plant-parts evades the necessity of the use of expensive metal salts. Various parts of plants, e.g., flowers, leaves, and seeds act as a gelling agent, chelating agent, reducing agent, and capping agent during reactions. This is a non-toxic, eco-friendly, and cost-effective method. The samples were characterized using various Advance Materials Characterisation Techniques. The results were very much in agreement with the desired values. In a few cases, better antibacterial activities have been observed with ferrites obtained via this method. Left-over parts of food and fruits can be used for this method which may help in waste management. Still, the tremendous scope is left in this area that can be exploited which may include scaling-up of the product.
Visualizing Non-Covalent interactions between Propylamine and 2-Chlorobenzyl alcohol in Benzene: Theoretical and Dielectric relaxation studies
Authors: Aravinthraj M , Liakath Ali Khan F , Sakthimani P , Udayaseelan J
Published: July 2021

The non-covalent interactions of propylamine (pa) with 2-chlorobenzyl alcohol (2cbOH) in benzene have been studied by theoretical and dielectric relaxation studies. In the theoretical method, the optimized structure of pa2cbOH is achieved by the DFT method in B3LYP/6-311++G (d,p) basis set at ground level d,p orbitals. The Vibrational energy distribution analysis is adopted to find the vibrational assignment of pa2cbOH, as well as it compared with the experimental observations. Stability, electronic effects are determined through the chemical reactivity parameters with the help of FMO analysis. The hydrogen bonding and Vander Waals interactions of pa2cbOH are confirmed with reduced density gradient (RDG) isosurface. In Dielectric relaxation analysis, various dielectric parameters like ε′, ε″, ε0 and ε∞ were determined for five different mole ratios of pa2cbOH. Higasi’s single frequency equation and Gopalakrishna’s single frequency concentration variation methods are validated by measuring the multiple relaxation time τ1 and relaxation time τ2 for group rotation of pa2cbOH. The strength of hydrogen bonding and other weak interactions were determined using the values τ1 and τ2.
Pollution Index and Air Ion Variation in Different Vegetation area at the Rural Station Bhilawadi (16059’N, 740 28’E)
Authors: Patil G B , Pawar S D , Bhosale J L , Patil P G
Published: July 2021

All are surrounded by air ions which shows the good and bad impact on us. These airborne particles have charge and conductivity. These are positive and negative air ions. The negative air ions have a positive effect on human health. We feel happy, relaxed, and breath easily due to them. But positive air ions are responsible for discomfort, headache, high blood pressure, nervousness in human life. The air ion concentrations in Grape, Sugarcane, Chickpea, and Onion vegetation in rural area Bhilawadi (16059’20” N, 74028’2” E) is measured with the help of a Gerdien condenser-based air ion counter developed and designed at A.C.S. College, Palus. Temperature, humidity, transpiration, radon exhalation, wind speed is responsible for variation in air ions. Onion, sugarcane, grapes, and chickpea have a higher concentration of negative air ions than positive air ions. Ionization by cosmic rays and gamma radiation is almost constant in daily cycles. Air ion concentration near the ground varies mostly with the exhalation of 222Rn and its progenies. Due to ionization, photosynthesis, transpiration, and radon exhalation process of vegetations ion concentration are different. The pollution index and air ion assessment coefficient show good air quality of sugarcane and onion as a natural air ionizer.
A Concept Proof Approach for Conversion of Leaf Litter into Humus with The Help of Self-Aerated Composting Units
Authors: Banupriya D
Published: July 2021

About 68% of leaf litter conversion into humus was attained within 30 days using composting technology, which was made possible by employing the perforated composting unit for self-aeration developed by the author Saveetha School of Engineering campus. It can be related to conventional composting system CHs, but comparatively, it takes longer than these self-generated units to attain the same output say 60days. The self-generated composting units once achieved a sustainable environment and did not show any sign of stress on them since moisture maintenance was done regularly. Within the first 10 days of service of the composting machine, efficiency was under 17%, which might be because the micro-organisms needed time to become acclimatised to feed, which was more texture-hard and nutrient-leaner than the feed (cow dung) the organisms used to feed. In comparison, cow dung has to be supplemented even higher (50% or more). As the days passed by, there was a dramatic rise in humus conversion efficiency, which reached near the ultimate of 100% by the end of 70 days. Overall, the humus production increased with time in a linear fashion in Figure 1; the regression-correlation being significant at r2 = 0.99.
Exploring the Research Trends in COVID-19 in Collaboration with Industry 4.0 Technology as an Indispensable Effective Tool to promote Global Health through Bibliometric Analysis
Authors: Divekar Neha , Itankar Nilisha , Malge Shilpa
Published: July 2021

Objective: Currently, the entire world is dealing with a lethal crisis caused by COVID-19. SARS-CoV-2 is the root cause of the new disease Coronavirus. Novel Coronavirus has gripped more than 215 countries and territories worldwide. This study provides the bibliographic analysis of data on the epidemiological research conducted on COVID-19 and technology-based tools and applications extensively used to study and interpret the Coronavirus to tackle the pandemic in every way possible. Method: We investigated the data from the Scopus search engine, Google Scholar, and World Health Organization (WHO) using associated terms like Coronavirus, COVID-19, Artificial Intelligence (A.I.), Machine Learning (ML), Big data, Internet of Things (IoT). The data stretches from December 2019 up to 9 May 2020.Result: A.I., an ML-supported platform, is used by many agencies worldwide. Out of 217 publications from 57 countries, China and United States contributed maximum technology-based research articles in correlation with COVID 19. Conclusion: The world is in the middle of a pandemic due to COVID-19. Globally human health has been impacted. This paper attempts to understand the intellectual pattern of COVID-19 and 4.0 industry tools in research using the Scopus database and conducting the bibliometric analysis. This bibliometric analysis would also facilitate future researchers’ pathway to identify research carried out in COVID-19, focusing on A.I., ML, and advanced digital technologies.It would develop the existing knowledge potential and help future researchers collaborate and facilitate interdisciplinary research to tackle the pandemic better.
An Efficient Scheme for Reliable File Transfer using Residual Link Lifetime Estimation based on Sparse Vehicular Routes
Authors: Pasha Mohammad , Farooq Mohd. Umar , Ramsha Alfia Ameena
Published: July 2021

Abstract. Location based networking protocols in Vehicle Ad-Hoc Networks (VANETs) employ the hopping strategy to acquire the route to a destination node. One of the commonly used methods is to select the vehicle that is nearest to their destination. This greedy transmission approach leads to packet drop in disruptive networks like VANETs, since it doesn’t take account of the quality of the newly-established links. In this article, a new method is proposed for identifying the next-hop node from a potential set which takes account of the remaining life of the contact connections combined with the vehicular movement. Compared with the existing idea of predicting the new location using Kalman filters, the proposed method is based on vehicular density in the path to destination.
A Conceptual Framework for Secure Cloud Migration
Authors: Ahuja Srishti , Nisha T N
Published: July 2021

Cloud computing is a budding web-based technology that tends to prevail in our environment, especially in the areas of computing and information technology that require large-scale network computing. Cloud computing is a shared set of services gaining popularity due to its profitability, availability, and high production. Just on the security grounds, cloud computing’ immense potential cannot be overlooked: ongoing research and the investigation of consistent, robust, and integrated cloud computing security models may be the solitary motivational pathway. There are three service and four deployment models in cloud computing. Cloud computing, together with its several advantages, also brings a much more difficult condition concerning privacy, authenticated access, data protection, etc. Because of these problems, the acceptance of cloud computing is becoming difficult in the current era. In this study, several security concerns related to reliability and data privacy, main aspects impacting cloud computing, were tackled, and recommendations on specific areas were also discussed.
Blockchain Technology Empirical Studies on the Demand of Distributed Network
Authors: Mishra Manish Kumar , Balamurugan M , Reena Roy R , Amanullah M , Shantha Shalini K
Published: July 2021

Blockchain technology has become a new model for encryption, unsustainability and confidence in both consumers and suppliers (SPs) in order to increase the quality of services. A game theory framework is used to simulate a competitive market with the existing platform controlled by a centralizer as a confidant third party to provide an economic overview of such a Blockchain-based platform sector. The portals serve as a mediator in this industry and provide consumers with services delivered by SPs. The key reasons for blockchain based network market performance are I how engagement by SPs represents its service efficiency (QoS) and (ii) how SPs are empowered to contribute their services, such as the virtual environment. A non-cooperative two-stage competitive game is used in our game formulation, whereby the first stage model how to promote SPs on a blockchain basis and the second stage modeleves rivalry between platforms to draw consumers. We therefore have an equilibrium analysis that offers a valuable description of the effect on competition among platforms and SPs’ equilibrium reward policy of the service quality of the blockchain network. Our numerical analysis reveals that the incentive to balance is increasing proportionately to the Fault tolerance of a blockchain-based network when the incentive is unfavourable if the number of participating SPs has a non-increasing QoS.
Augmentation of SECaaS model with eCISO in cloud-based security services: A Comprehensive study
Authors: Saxena Siddharth , Nisha T N
Published: July 2021

In today’s competitive world and the time of business discontinuity and falling economies due to many reasons, enterprises worldwide are trying to process business data securely and minimize IT systems’ operational cost with technologies in cloud computing. With the benefit of cost-efficiency in cloud services, there are some concerns regarding IT security, IT governance, and compliance, which plays a vital role in the business as usual. Security as a service model is a cloud-based security service model to provide secure environments, mediums, and systems to enterprises. In this paper, we are attempting to introduce a new service model to cloud-based security platform and perform a comprehensive study with augmenting security as a service (SECaaS) model with eCISO services for better governance of risks and decision making related to IT security to optimize the service model to help out CEOs and CIOs to ensure the security of their IT systems and data.
Edge Computer-Enabled Internet of Vehicle Applications with Secure Computing and Load Balancing
Authors: Majumder Darpan , Mohan Kumar S , Ashoka D V , Shajin Naragunam A
Published: July 2021

In recent years, the Network of Automobiles has attracted great interests. Several IoV applications have been developed to improve road safety, performance and comfort. A virtualization is a common tool for disruption streaming video. However, cloud computing can cause undue delays in applications sensitive to progressive delays, such as auto/assisted driving and emergency error handling. The beneficial technology is edge computed, which expands processing and storage capacities to the network’s periphery. Throughout this report, we merge mobile agent networks or fixed-point processing domains into defined road networks to establish collaboration for all these machine and intensity implementations in IoVs. IoV is designed to optimize the use of these stratified boundary computation strengths in the idea of technology communication and communication technologies. Moreover, the loss of all nodes and communications, which can have life-threatening implications, is possible in an IoV system that is complicated and dynamic. We are integrating both partial computing offloading and consistent job assignments with a reprocessing system for EC-SDIoV to ensure the IoV services’ fulfilment with high reliability. Since the problem of optimization is built to optimize latency durability by the faulty tolerant particulate swarm protocol. The performance appraisal findings validate that both latency reduction and stability are still feasible under the current scheme.
Challenges in Single Sign-On
Authors: Pandey Prashant , Nisha T N
Published: July 2021

Single sign-on uses a centralized session concept, and it is a service that authenticates one and one-on-one designated platform. Later, with this, we can use various services and products without logging in every time. However, there are sure demanding situations in implementing SSO. Business enterprise no longer is most effective and needs to integrate user network logon with a nearby application and software program (SaaS) cloud offering. Simultaneously, in an enterprise, SSO’s centralized solution does not include all the users, applications, devices, and equipment. Another undertaking from the records angle is that the user can log on outside SSO answers. Its user identification may also exist in exceptional forms. Simultaneously, the enterprise desires to cope with bequest desktop programs that do not coordinate with users’ listing logins which may be the frail hyperlink that reasons SSO to fail in the company. With the efficiently applied SSO and designing framework keeping in mind the challenges, we can enable and disable users to enter more than one system, platform, apps, and different resources. Also, it may effectively resolve and dispose of the problem of password-related downtime and reset expenses. Simultaneously, it removes the danger of threat from an insider, improves authentication processes and user experience, delivers authority to the company, and simultaneously provides them with the right of entry to firmly on top of the user’s things.
Usability of Blockchain Technology in Higher Education: A systematic review identifying the current issues in the education system
Authors: RushabhBalpande  , Patil Kanchan
Published: July 2021

Blockchain facilitates the creation of a shared document of a digital transaction in a distributed way where no third-party regulates any data or related activity. Earlier blockchain was used to transmit money, but today it has a huge scope of utilization in various domains like banking, health care, the Internet of Things (IoT), and many more. Inside the educational domain, blockchain offers many circumstances for disperse administration of records in an interoperable way in higher educational institutions. The primary purpose of the study is to address the current issues relevant to educational institutions and to identify the appropriate blockchain characteristics that can solve these issues. To recognize and extract significant knowledge from the selected research studies, a systematic literature review approach has been followed by us. Our research study represents the current problems in three forms, i.e., financial, digital, and physical. The consequences of the study show that the main problems faced by education institutions are the risk of manipulation, the tough of authenticating, and difficulty in interchanging records among institutions. This research analyzes the blockchain characteristics such as fragmentation, traceability, and consensus system, focusing on a few problems relevant in this domain.
Data Communication through Reliable Sensor using Huffman Coding System
Authors: Padmanaban K , Senthil Kumar A M , Velmurugan A K , Madhan E S
Published: July 2021

Wireless sensor networks (WSNs) contain amount of sensor nodes that can forecast the atmosphere to transmit the information in unfavourablesituations. Though, restricted efficient also security problems in WSN. To solve these problems this paper Data Communication through Reliable Sensor using Huffman Coding system (DCRS) is introduced. In this strategy, the node with highest remaining energy will getdivision in the information transmit procedure. Security foreachhop node is accessiblethrough binary hop count (BHC) also verification is specified utilizing Huffmancoding to avoid the malicious as well as other attacks in the network. The DCRS strategy is formalized through a network simulator.
Deep Analysis of Covid-19 Receptors Recognition and Locating In Pulmonary Ultrasound
Authors: Sivagami S , Divya J , Sailaja P , Jagadish Kumar N
Published: July 2021

In the course of the latest COVID-19 flu epidemic, several projects have been carried out to test LD-based strategies for the helping diagnosis of lung diseases. Deeper learning (DL) has proven its effectiveness in radiography. Although the present study relies on CT scans, DL strategies for interpreting pulmonary ultrasound (LUS) images are being used in this article. In specific, we present a new, completely annotated LUS data collection obtained from multiple Italian institutions with labels showing the level of disease intensity in a shot, photo, and digit optimization mask. By using these data, we implement numerous profound models that deal with the related tasks of automated LUS image analysis. We introduce a new deeper network derived from Space Converter Networks, that continuously estimates the extreme disease score for an input frame and weakly controlled the location of pathological machines. We implement also a new approach for efficient video-level averaging of frames based on uninorms. Finally, we benchmark deep state-of-the-art models for estimating COVID-19 biomarker pixel classification. Experiment was conducted on the planned dataset show satisfactory results for all the tasks considered which will pave the way for potential DL studies for the diagnosis of LUS-based COVID-19.
Artificial Neural Network for Rainfall Analysis Using Deep Learning Techniques
Authors: Nandakumar S D , Valarmathi R , Sudha Juliet P , Brindha G
Published: July 2021

The estimation of rainfall is one of the most critical and daunting challenges in today’s environment. Weather and rainfall are typically extremely nonlinear and dynamic, needing sophisticated machine models and simulation for forecasting accurately. The economy of India is agriculture and is focused primarily on crop production and precipitation. Predictions of rainfall are important for all farmers to assess crop productivity. Rainfall forecast involves the application of science and technology to determine weather conditions. In order to utilize water supplies efficiently, the crop productivity and the pre-program of water systems, it is necessary to determine the precipitation in detail. The actions of such nonlinear processes can be modeled using an Artificial Neural Network (ANN). Most researchers in this area have been effectively utilizing ANN for the past 25 years. This article offers you an summary of some of the methodologies valid for using ANN for rainfall prediction by numerous researchers.The survey also states that forecasts of rainfall using ANN technologies are more accurate than conventional mathematical and numerical approaches.
RETRACTED: Development of a Prototype Power Distribution Misuse Monitoring System
Authors: Prabahar Godwin James T , Ganesan R , Kumar Pardeep , Perumal P
Published: July 2021

In order to satisfy the rising need for efficient energy Synchro phasor systems have a vast data volume for wide-range tracking and power system operation. In the context of the big data problem, the design of conventional intrusion detection systems, using rules manually generated on the basis of expert expertise, is know-how intensive. This article introduces a clear and integrated approach to developing a hybrid IDS which learns temporary transmission line requirements including disruptions, showed normal processes and cyber-attacks. A machine learning algorithm called general trajectory mining is used to learn patterns for situations by fusing synchrophasor calculation data with power system audit logs automatically and reliably. An IDS prototype has been developed and validated as a proof of concept. For a multiple, seven power transmitting devices, the IDS prototype classifies disruptions, regular control operations and cyber assault correctly for distance security.
Content-Based Image Retrieval Techniques: A Survey
Authors: Sivakumar M , Saravana Kumar N M , Karthikeyan N
Published: July 2021

In these eras, digital day’s cell smartphones and cameras are gaining a titanic reputation, resulting in the speedy growth of virtual images that are available throughout the internet. With an exponential boom within the image sizes, databases in different media lie an extremely good project for massive scale image search. Image retrieval from databases or the internet wishes an unsuccessful and effective technique because of the explosive increase of digital snapshots. Image recovery is known to be a comprehensive research area, particularly in content-based image retrieval (CBIR). CBIR retrieves comparable photographs from a huge photograph database primarily based on photo features, which has been totally lively study vicinity recently. The content materials that may be derived from images which include color, shade, texture, shape, are used for retrieving an image from the database. This paper will provide a survey and discuss the contemporary literature of various sorts of image retrieval (IR) structures and comparisons among them.
Classification of Diseases in Paddy using Deep Convolutional Neural Network
Authors: Malathi V , Gopinath M P
Published: July 2021

Paddy disease detection is decisive in the field of automatic pathogens diagnosis machine. Currently, Deep Con- volutional neural network typically examined the state-of-the art results in image classification. In this work, we proposed a novel DCNN model to identify previously known bacteria leaf blight, brown spot, leaf blast, leaf smut and narrow diseases in prior knowledge. A unique repository of data holds 1260 images of different diseases, 80% of data carried out for training and 20% for testing the samples. To add advantages to our model, we built our model using ADAM optimizer and conducted comparative research over SVM (support vector machine), KNN (K-Nearest neighbor) and ANN (Artificial Neural Network). The dataset given to the novel DCNN model with keras framework and achieved testing accuracy of 0.940 with less training error rate of 0.013. The interpretation outcome demonstrates that high level image classification accuracy with less error rate was achieved by novel DCNN model than traditional methods. Therefore, our model performs best for recognizing 5 paddy diseases and can be possibly implemented in day to day life application.
Smart Door Lock to Avoid Robberies in ATM
Authors: Sidda Reddy V. , Kalli Sivanagireddy , Gebregziabher Haftom , Ravindra Babu B.
Published: July 2021

In the present situation, the ATM system is used by most of the population to withdraw currency. The number of ATM Centers is growing increasingly as social computerization and automation are dramatically increasing. Simultaneously, even though the CCTV cameras are installed in the ATM cabins, many ATM thefts have happened in many locations. It is also important to adjust the protection framework. We present a protection mechanism for ATM robbery by using intelligent & powerful technology to minimize these forms of robberies. This scheme also analyses different physical assaults on ATMs. We would use a Wireless Sensor Network in our proposed framework to track the theft and catch the criminal & hand them over to cops in a specific area. USB Camera for the recording & transmitting of the face of the person operating the ATM locker. Tilt and vibration sensors are used to identify the unusual behavior performed on the ATM system. Tilt and vibration sensors are used.
On To A Centralized Sponsorship of Blockchain Based IoT Operational Infrastructure
Authors: Josephine M S , Balasubadra K , Kevin Andrews S , Lakshmi Narayanan K
Published: July 2021

With the rapidly developed IT technology, large-scale networks can be designed to link many heterogeneous devices into the Internet. The majority of current infrastructures are clustered, easier to maintain, but cannot efficiently provide immutable and verifiable service between multiple parties. For large-scale infrastructures like decentralization, reliability, trackability, and immutability, Blockchain technology offers several desirable functions. This article introduces an infrastructure based on blockchain that facilitates unchanging and controllable services. However, the need for storage capacity presents a threat to resource-controlled architecture when adding blockchain technologies to the infrastructure. The paper attempts to tackle the storage dilemma with a centralized storage side chain. In fact, the proposed architecture has a distributed storage structure where most of the blockchain is kept at the cloud, although these current blocks are kept in the real network integration node. The framework architecture allows the local, blockchain and server infrastructures to be conveniently merged to create a distributed blockchain storage between two connectors, the database and the blockchain. The extended version blockchain connection builds block of the network info, and addresses network/cloud overlay sync problems in blockchain. In a practical case of professional IoT, we also have a test case to demonstrate the reliability of the general architecture processing blockchain.
Dimensionally improved residual neural network to detect driver distraction in real time
Authors: Balamurugan M , Kalaiarasi R
Published: July 2021

Bountiful reasons are there for crop up of road accidents. Predominantly most of the road accidents are turn out by the humans. In compare with other sources of road accidents, distracted driving is the foremost one. Driver gets distracted ascribed to many factors such as texting using phone, seeing outside of the car. The regime can grasp the road accidents by enforcing the traffic regulations moreover the regime seeks the assistance from the technology to reduce the car accidents due to driver distraction. There are numerous research undergoing to reduce the chance of the driver to get distracted by monitoring the physical activities of the driver while driving the four wheeler. Automatic detection of driver distraction can support to develop an apprise system by observing the activities of the driver that provide better result and evading the car accidents. Deep learning is a leading technology in automated industries to detect the traffic light signs and pedestrians. The novel ResNext
101
is the proposed work and inherited from its parent model called Residual Network (ResNet) to train and test the model. The “Next” in the word ResNext represents next dimension of ResNet called as “cardinality”. In this paper, with the help of Convolutional Neural Network (CNN), the system detects and captures the distracted moments of the driver from proper driving gestures automatically in the form of 2D image. The test results of the model outperforms and proved its significance over the existing driver detection algorithms by bagging higher efficacy with 97.6% accuracy in classifying the live driver posture.
Geospatial Analysis of the Dynamics of Climate in Kolkata Metropolitan Area
Authors: Talapatra Adrita , Majumder Arijit , Das Sandipan
Published: July 2021

The Kolkata Metropolitan Area region comprises urban towns that have witnessed major changes and have been exposed to urban agglomerations, population outbursts, and have faced difficulties in regional management. The growing cities comprising these areas thus faced various kinds of natural changes. One of the major significant changes included the change in climaticconditions. Climateis the weather experienced by any region for a long period, particularly extending to 30-35 years. Therefore, the climate is a long-term study of any region where any slight change shows a significant impact on the lives and balance of the region’s habitats. This paper tries to deal with the analysis of climate change in the KMA region. Metropolitan cities in India are currently considered prime concerns due to various climatic distortion and global warming effects. Thus, the paper tries to show the factors and effects of climate change. The study period has been taken for 35 years in the paper. The analysis is carried out using various GIS techniques using the ArcMap 10.1.1 software and statistical techniques to generate graphs. From 1989 to 2006 ranged high as the population showed a rising trend in Kolkata, Howrah, and Kalyani.However, this trend changed for some time during 2014 and 2015 as various plantation activities, programs, and projects were taken up by the government to safeguard climate change’s harmful effect. It shows a rise in the temperature and fall in the rainfall quantities from 2015 to 2019. It also shows the disturbed rainfall pattern as a characteristic feature in the KMA cities as sudden droughts or urban flooding rise as a common phenomenon. The area is highly exposed to constant modifications. The paper concludes in a nutshell how the changes have affected the region and are still having asignificant impact on influencing lives and living.
A Modified Hybrid Blockchain Framework for Secured Data Transaction
Authors: Bhanupriya P , Gauni Sabitha , Kalimuthu K , Manimegalai C T
Published: July 2021

Blockchain has recently become an essential tool which enables sensitive cloud services without the need for central confidence. For example, several different cryptocurrencies were permitted with public blockchains. Unfortunately, confidential details may be exposed on current public blockchain and smart contracts implemented there. Whilst some continuous work is under way to resolve these insecure knowledge leakage problems using advanced cryptography, they need major improvements on current and common Blockchain technology such as Ethereum and are typically costly in computing. On the other hand, blockchain applications were proposed to allow the data exchange among the pre accepted nodes/participants to be more efficient and privacy-preserving. While private blockchains respond to certain challenges of privacy by allowing only the particular community of participants to view sensitive data, they do not allow public transparency for communications because businesses are accepted by a known number of users also cannot be freely viewed. One natural problem is whether we should use public and private Blockchain networks in order to allow effective, improve privacy and accountable applications in view of these findings? In this work, we try in connection with digital auctions to face this challenge. In specific, we provide a newly designed blockchain architecture combined with private and open blockchains which enables sensitive offers to be opened up on a secluded blockchain so solitary the merchant can study the offers, and none of others. We also use shared blockchains to report the public sale winner and to make transfers responsible. Moreover, we demonstrate how we can promote sincere activity among auction participants by using intelligent contracts on public blockchains. Our detailed analytical findings suggest that it’s more cost effective compared to pure public auction implementations based on blockchain.
Automated Vision Defect Detection Supported Deep Convolutional Neural Networks
Authors: Lalitha S , Shanthi N , Gopinath S
Published: July 2021

They should more truly detect abnormalities in the refractive error, used to prevent the children of amblyopia, which can lead to permanent visual impairment, but at first it was detected. A variety of tools have been adopted to protect the area of amblyopia more easily. Amblyopia is a lifetime serious eye disease. Amblyopia contributes to forecasting and treatment and rapid public treatment. They are also useful for completely automatic detection of amblyopia deep neural networks. A tele amblyopia dataset is used for detection. Then proposed deep convolutional neural networks are used for automated amblyopia detection on tele amblyopia dataset. The proposed algorithm comprises of 2 phases. In the first phase, the Enhanced Firefly Algorithm (EFA) is used to segment the eye region. In second phase, a DCNN is designed and trained to classify the segmented eye areas as amblyopia or normal. The test comes about appear that the proposed strategy can work well with the programmed discovery of amblyopia.
Moving from Detection Centric to Prevention Centric Security Using Automation: A Survey
Authors: Sravanthi RVS , Nisha T N
Published: July 2021

In the present time, cybersecurity plays a crucial role in every aspect. Protecting data, hardware, software alone is not sufficient as the technology is growing exponentially and information is easily available. Regarding artificial intelligence data, Sentinel One platform, endpoint security shows that from February 20, 2020, to March 17, 2020, the trend was in an upward motion, as the attacks attempted has peaked to 145 threats per 1,000 endpoints, in comparison to 31 or 38 at the start of that period. According to the Q2 2018 Threat Study, the quarterly report by Nexus guard, the average denial-of-service (DDoS) attack grew to more than 26Gbps, up 500 percent in scale. Regardless of the complexities of the modern cyber climate, stereotypic defense solutions do not fulfill the information security requirements. Earlier detection techniques were sufficient to protect the cyber environment, but due to growing cyber threats such as Ransomware, malware, DDoS, we need strong protection techniques to restrict the threat’s entry. Given this context, this study explains the evolution of the Preventive techniques and detective techniques; both the approaches are complementary, which would be discussed in this paper by considering Automation Technology. It introduces the survey of various Automation Technologies implemented for the advancement of prevention-centric security. Based on the evaluation metrics, the selection of better technology is concluded.
Fingerprint Presentation Attack Detection Approaches in Open-Set and Closed-Set Scenario
Authors: Gupta Anshdha , Verma Akhilesh
Published: July 2021

In the biometric system, fingerprints are widely used to recognise an individual’s identity and are vulnerable to presentation attacks such as spoofing. Spoof fingerprints are fake fingerprints created using artificial materials like play-do, silicone, etc., which fool the biometric identification system. Spoof handling is an urgent need nowadays, as these attacks’ success rate is more than 70%. Much work has been done on fingerprint spoof detection, but mostly involved closed-set problems, i.e. spoof materials used are the same for training and testing set, but they face poor generalisation problem. Hence to overcome closed-set problems, Open-set solution came into existence in which some novel spoof materials were introduced in the testing set, which was not seen during training. This paper will give a brief review of various closed-set and open-set solution techniques along with the tabular view of their Average Classification Error (ACE) scores.
Applying data mining technique to predict trends in air pollution in Mumbai
Authors: Sadhasivam Jayakumar , Muthukumaran V , Thimmia Raja J , Vinothkumar V , Deepa R , Nivedita V
Published: July 2021

Prediction of air quality is a topic of great interest in air quality research due to direct association with health effect. The prediction provides pre-information to the overall population of the area about the status of pollution on which they can take precautionary measures and can protect their health. The problem arises when the level of SO2, NO2 and residual suspended particulate matters in the air increases than that of theirs restricted level. In this paper, the Prophet Algorithm, open source software, is applied to predict the trend of air pollution in the city of Mumbai, Maharashtra. The Prophet is machine learning algorithm to forecast and also to predict time series data. It is based on additive model where non-linear trends are fit with yearly and weekly seasonality. The graphical results are generated after using this algorithm which shows the trending pattern of the pollutants in the air of Mumbai.