bluuebunny/crossref_metadata_2025_split huggingface dataset:
Binary Black Hole Automated Identification by Agglomerative Clustering based on Gravitational Waves
Authors: Adhikary Subhrangshu , Banerjee Saikat 
Published: December 2021

Abstract
The General Theory of Relativity, proposed by Albert Einstein theoretically predicted that very large accelerating mass creates ripples in spacetime which is the strongest for merging binary black hole system and the ripples can travel billions of light-years and these ripples are called Gravitational Waves. By the time these waves reach Earth, they become very faint and can’t be detected with regular methods. For this, LIGO has created specialized detectors based on the laser interference principle to detect strains caused by gravitational waves in e-19 scale. GW190521 is a gravitational wave event recorded on 21 May 2019 at 03:02:29 UTC and caused by the merger of two black holes of 85M© and 66 M© whose progenitor was the largest ever recorded. Throughout literature, very few amounts of autonomous black hole identification models have been made because of limited data availability. This experiment proposes methods for autonomous identification of black holes by using an unsupervised machine learning algorithm called Agglomerative Clustering with very little data to train which can adapt quickly to gravitational wave events. The model could be easily deployed near laser interferometric observatories for autonomous black hole identification with minimal effort.
Development of Smart Earth Leakage Circuit Breaker Using IoT and Power Electronics
Authors: Mehta Rashesh , Saiyad Junaid , Smart Niyatee , Mali Gordhan , Kamat Vithal 
Published: December 2021

Abstract
The Smart Earth Leakage Circuit Breaker research is based on IoT& power electronics-based protective switchgear for domestic consumers for the protection against earth leakage faults. In this paper, we have shown how to create a custom web server using HTML and CSS language and hosting this webserver to ESP module using Serial Peripheral Flash File System (SPIFFS). Along with protection against earth fault it provides, controlling of tripping current or fault current, monitoring voltage, power, current, power factor parameters of the connected load, monitoring fault parameters, Indicating the device status whether the ELCB is on or off, and the condition of ELCB it is in faulty condition or healthy condition and to let the user set the value of the tripping current on the webserver at which the ELCB must trip.
Review of enhanced power quality using unified power flow control system in electrical network
Authors: Shende Divya , Jagtap Prashant , Hiware Rutuja 
Published: December 2021

Abstract
Flexible FACTS system of AC transmission. FACTS Devices can regulate electricity flow, develop the transmission capacity for power management. UPFC is a multipurpose fact controller carried on design of the constant voltage source. As an electrical device UPFC for rapid reactive power adjustment on high voltage electricity transport grid. Unified power flow control (UPFC). The latest FACTS gadget is UPFC. This combines series and shunting compensator characteristics and enables Power reactive and response to be controlled. UPFC utilization reduces difficulties in power quality including voltage sink and voltage surge. This article addresses UPFC and also several novel topologies for FACTS controllers.
Enhanced power quality using unified power flow controller systems
Authors: Shende Divya , Jagtap Prashant , Hiware Rutuja 
Published: December 2021

Abstract
Electrical system frequently finds and issue due to unstable nature and power quality because of, in relation to great number of nonlinear charges. So, there is need to limit inside of these difficulties and produce fine voltage quality concerns. The Flexible Alternate Flow Transmission Systems (FACTS) are the framework made out of static gear works for the AC transmission of electrical energy. Unified_Power_Flow Controls (UPFC) are the excellent FACTS tools to attach series and shunt together and it could use for framing Power transmission sensitive and active power. Here in the paper, Unified Power Flow Control (UPFC) used to clear the voltage sink and Surge. Unified Control was developed and engineered using amplifiers and rectifiers. The real and reactive modifications in congruous control orientations at the receiver side. Use of Simulink of MATLAB checks quality of energy in the use of Unified Control.
A new design of control & power management strategies of hybrid ac-dc microgrids toward high power quality
Authors: Chaurase Payal , Ramtekkar Pankaj 
Published: December 2021

Abstract
The micro grid idea provides for the lack of several reversing switches to unitary AC-DC grid that enables connection and charges (loads) to the electrical systems with changeable regenerative AC and CC sources. Safe operation and gadget safety involve digital integration with utilities/grid through power converters. Enhanced client reliability, decreased input losses, local voltages are supported, and waste heat efficiency increased, voltage drop or interruptible supply of electricity can be customized to satisfy their unique customer demands. Work at present Analyses the performance in grid tie mode of hybrid AC/DC systems. Here are PV systems, PV systems, For the construction of microgrids wind turbine generators and batteries are employed. Convert procedures for the correct coordination of AC sub-grids to DC subs-grids have also been established for converters. MATLAB/SIMULINK environment results are generated.
IoT Enabled Smart Lighting System for Smart Cities
Authors: Dankan Gowda V , Annepu Arudra , Ramesha M , Prashantha Kumar K , Singh Pallavi 
Published: December 2021

Abstract
The pace of urbanisation has risen tremendously during the last few decades. To provide a higher quality of life, urban dwellers will require a greater variety of improved services and apps. The term “smart city” refers to integrating contemporary digital technology in the setting of a city to improve urban services. There are possibilities to create new services and connect disparate application areas with each other as a result of the use of information and communication technologies in the smart city. However, to make sure the services in an IoT-enabled smart city environment remain running without depleting valuable energy resources, all of the apps have to be maintained using energy resources that are kept at a minimum. IoT can enhance a city’s lighting system since it uses more energy than other municipal systems. An intelligent city integrates lighting system sensors and communication channels with enhanced intelligence features for a Smart Lighting System (SLS). To control lighting more efficiently, SLS systems are built to be autonomous and efficient. We cover the SLS and evaluate several IoT-enabled communication protocols in this article. Furthermore, we evaluated several use scenarios for IoT enabled indoor and outdoor SLS and generated a report detailing the energy consumption in different use cases. By using IoT-enabled smart lighting systems, our research has shown that energy savings are possible in both indoor and outdoor settings, which is equivalent to a forty percent reduction in energy usage. Finally, we went through the SLS in the smart city research plans.
Smart Agriculture and Smart Farming using IoT Technology
Authors: Dankan Gowda V , Sandeep Prabhu M , Ramesha M , Kudari Jayashree M , Samal Ansuman 
Published: December 2021

Abstract
It has become easier to access agriculture data in recent years as a result of a decline in digital breaches between agricultural producers and IoT technologies. These future technologies can be used to boost productivity by cultivating food more sustainably while also preserving the environment, thanks to improved water use and input and treatment optimization. The Internet of Things (IoT) enables the production of agricultural process-supporting systems. Referred to as remote monitoring systems, decision support tools, automated irrigation systems, frost protection systems, and fertilisation systems, respectively. Farmers and researchers must be provided with a detailed understanding of IoT applications in agriculture as a result of the knowledge described above. This study is about using Internet of Things (IoT) technologies and techniques to enhance agriculture. This article is meant to serve as an introduction to IoT-based applications in agriculture by identifying need for such tools and explaining how they support agriculture.
Stress Recognition Using Facial Landmarks and Cnn (Alexnet)
Authors: Ramesh Naidu P , Pruthvi Sagar S , Praveen K , Kiran K , Khalandar K 
Published: December 2021

Abstract
Stress is a psychological disorder that affects every aspect of life and diminishes the quality of sleep. The strategy presented in this paper for detecting cognitive stress levels using facial landmarks is successful. The major goal of this system was to employ visual technology to detect stress using a machine learning methodology. The novelty of this work lies in the fact that a stress detection system should be as non-invasive as possible for the user. The user tension and these evidences are modelled using machine learning. The computer vision techniques we utilized to extract visual evidences, the machine learning model we used to forecast stress and related parameters, and the active sensing strategy we used to collect the most valuable evidences for efficient stress inference are all discussed. Our findings show that the stress level identified by our method is accurate is consistent with what psychological theories predict. This presents a stress recognition approach based on facial photos and landmarks utilizing AlexNet architecture in this research. It is vital to have a gadget that can collect the appropriate data. The use of a biological signal or a thermal image to identify stress is currently being investigated. To address this limitation, we devised an algorithm that can detect stress in photos taken with a standard camera. We have created DNN that uses facial positions points as input to take advantage of the fact that when a person is worried their eye, mouth, and head movements differ from what they are used to. The suggested algorithm senses stress more efficiently, according to experimental data.
Convergence and Stability Results of Modified CUIA Iterative Scheme for Hyperbolic Convex Metric space
Authors: Gonder Surjeet Singh Chauhan , Basra Khushboo 
Published: December 2021

Abstract
The iterative fixed points have numerous applications in locating the solution of some real-life problems which can be modelled into linear as well as nonlinear differential and integral equations. In this manuscript, first of all, a new iterative scheme namely Modified CUIA iterative scheme is introduced. We first prove a theorem to check the convergence of this iteration for Hyperbolic Convex metric space. The result is then supported with one example. Further, another theorem is proved establishing the weak T stability of modified CUIA iterative scheme on the above space.
A Text Mining using Web Scraping for Meaningful Insights
Authors: Reddy C Kishor Kumar , Anisha P R , Gia Nguyen Nhu , Sreelatha G 
Published: December 2021

Abstract
This research involves the usage of Machine Learning technology and Natural Language Processing (NLP) along with the Natural Language Tool-Kit (NLTK). This helps develop a logical Text Summarization tool, which uses the Extractive approach to generate an accurate and a fluent summary. The aim of this tool is to efficiently extract a concise and a coherent version, having only the main needed outline points from the long text or the input document avoiding any type of repetitions of the same text or information that has already been mentioned earlier in the text. The text to be summarized can be inherited from the web using the process of web scraping or entering the textual data manually on the platform i.e., the tool. The summarization process can be quite beneficial for the users as these long texts, needs to be shortened to help them to refer to the input quickly and understand points that might be out of their scope to understand.
False News Recognition Using Machine Learning
Authors: Thirupathi Lingala , gangula Rekha , Ravikanti Sandeep , Sowmya Jujuroo , Shruthi S K 
Published: December 2021

Abstract
In these modern times where internet has become widely popular and used by almost everyone, anyone can share or upload articles without any credibility. False news refers to articles that are published with the intent of deliberately misleading readers. In the recent times false news on internet has become more and it has become a major problem as it is difficult to differentiate between the real and the false news. False news and false posts have become more prevalent on social media sites such as Face book and Twitter. From these platforms the news will be spread like wild fire without any authenticity. It can be used to sway election outcomes against certain candidates, can be used for click baiting purposes, and can be used to earn revenue by misleading the users. In this paper we will use natural language processing techniques like bag of words and TD-IDF and machine learning concepts of classification algorithms like SVM and passive aggressive classifier to train our machine to differentiate false news from real news and we will compare the accuracy of methods used to find accurate model.
Factors influencing the use of Deep Learning for Medicinal Plants Recognition
Authors: Anchitaalagammai J V , Shantha Lakshmi Revathy J S , Kavitha S , Murali S 
Published: December 2021

Abstract
Medicinal plants are very essential in maintaining the physical and mental health of human beings. For providing better treatment, Identification and classification of medicinal plants is essential. In this research paper, main objective is to create a medicinal plant identification system using Deep Learning concept. This system identifies and classifies the medicinal plant species with high accuracy. In this system, five different Indian medicinal plant species namely Pungai, Jamun (Naval), Jatropha curcas, kuppaimeni and Basil are used for identification and classification. The dataset contains 58,280 images, includes approximately 10,000 images for each species. The leaf texture, shape, color, physiological or morphological as the features set for leaf identification. The CNN architecture is used to train the collected dataset and develop the system with high accuracy. As result of this model, 96.67% success rate in finding the corresponding medicinal plant. This model is advisable to use as early detection tool for finding the medicinal plant because of its best success rate
Monitoring Riders Pattern For Automatic License Issuing System
Authors: Harikrishna Kani V , Malarvezhi P. , Sharath R , Jeyaraman S 
Published: December 2021

Abstract
This paper presents about the mechanization of driving permit test framework and informing the aftereffect of the applicant remotely. Normally, in driving test an up-and comer applied for license need to drive over a shut hover path before the trained professionals. The up-and-comer needs to roll over the way with explicit guidelines and on the off chance that he neglects to do so he will be excluded and should attempt next time. These specialists watch the mistakes of the up-and-comers physically. In this paper, the Arduino framework with important sensor modules has been produced for viewing the contender for getting their permit. By utilizing this framework, the applicant who take up the test are checked and the outcome climate the competitor is passed or fizzled is refreshed to the up-and-comer just as the specialists remotely utilizing IOT and GSM modules. This checking of the driving test ground is done autonomously using the Arduino structure. This framework is produced for improving the norms of permit giving instrument to improve street wellbeing
Water Budget Estimation in Water Resources Management in Drought Prone Areas in Rayalaseema Region, South India
Authors: Kiran Kumar T. , Niveditha K. 
Published: December 2021

Abstract
Water is a valuable natural resource, fresh water is vital for health and to the economy, and reliable access to it is becoming increasingly important as the India’s population rises. Yet its availability is limited, per capita accessibility of useable water is depleting, but with increasing living standard of people, all around fast industrial development and expansion, necessity of fresh water is raising high continuously. Water audit is a successful tool for minimizing losses, working on different utilizations and in this way empowering water conservation in irrigation, domestic, power and industrial as well. Water audit controls the measure of water lost from a distribution system because of spillage and different reasons like burglary, unapproved withdrawals from the organizations and the cost of such misfortunes to the utility. Water budget is a bookkeeping of all the water that streams into and out of an undertaking region of project area. Water budget gives the financial aspects on the distribution of quantity of water in Rayalaseema region. The study area this paper to calculate the water budget in the study area of 51 Mandal of Rayalaseema region and based on the water quantity analysis to prepare water, soil conservation structures in study area, for effective water management
Fuzzy Congruence Relations in Generalized Almost Distributive Fuzzy Lattices
Authors: Sangeetha T. , Senthamil Selvi S. 
Published: December 2021

Abstract
This paper defines the fuzzy congruence relation of GADFL (Generalized nearly distributive fuzzy lattices). The ideas of θ - ideal and θ - Prime ideal are introduced in GADFL, and the fuzzy congruence relation is used to explain these ideals.
AMS subject classification: 06D72, 06F15, 08A72.
Analysis of Microgrid System with Photovoltaic Array
Authors: Ramamohan Reddy K. , Siddhik N. , Jyothirmayi A. , Kalyan Kumar K. 
Published: December 2021

Abstract
As the modern power system is advancing, new challenges are coming in to picture. The micro-grid concept along with renewable energy PV systems is emerging as a key factor for the long-term doable solution for future energy sector requirements. Micro-grid can have distributed energy resources like PV panels, wind turbines, Geothermal Tidal energy & power generators that produce power. Controlling and protection are the main problems that need to be handled in microgrid operation. Microgrids need to provide multiple end user needs simultaneously. For example, electricity generation, heating and cooling. This paper accords with the analysis of a Microgrid system connected with a PhotoVoltaic array.
An Efficient Interconnection System for Neural NOC Using Fault Tolerant Routing Method
Authors: Pradeep kumar A. , Devendar Reddy Y. , Srinivas Reddy T. , Jamal K. 
Published: December 2021

Abstract
Large scale Neural Network (NN) accelerators typically have multiple processing nodes that can be implemented as a multi-core chip, and can be organized on a network of chips (noise) corresponding to neurons with heavy traffic. Portions of several NoC-based NN chip-to-chip interconnect networks are linked to further enhance overall nerve amplification capacity. Large volumes of multicast on-chip or cross-chip can further complicate the construction of a cross-link network and create a NN barrier of device capacity and resources. In this paper, this refer to inter-chip and inter-chip communication strategies known as neuron connection for NN accelerators. Interconnect for powerful fault-tolerant routing system neural NoC is implemented in this paper. This recommends crossbar arbitration placement, virtual interrupts, and path-based parallelization strategies in terms of intra-chip communications for the virtual channel routing resulting in higher NoC output at lower hardware costs. A lightweight NoC compatible chip-to-chip interconnection scheme is proposed regarding to inter-chip communication for multicast-based data traffic to enable efficient interconnection for NoC-based NN chips. Moreover, the proposed methods will be tested with four Field Programmable Gate Arrays (FPGAs) on four hard-wired deep neural network (DNN) chips. From the experimental results it can be illustrate that a high throguput can obtained effectively by the proposed interconnection network in handling thedata traffic and low DNN through advanced links.
Publicly Verifiable Vibrant Digital Medical Information Systems
Authors: Anju Shaik Sumi , Sravani BSN , Madala Srinivasa Rao 
Published: December 2021

Abstract
As data processing advances, decentralized media has been widely recognized for its ability to store large amounts of data. By comparing a revisited content to a dispersed repository, a cloud provider may verify the document’s integrity without having to retrieve it. A reconsidered examining strategy is offered to lead the customer to reconsider the significant assessing task to third sector inspector, taking into consideration the important computing cost brought up by the checking process (TPA). TPA may be deterred by the primary revisited evaluating strategy, but the second plan gives the harmful organization the right of inspection over the readdressed data of users, which poses a significant risk to patient privacy. Human Emphasis for reconsidered inspection is presented in this work, which emphasizes that the service user can be overwhelmed by her own data. Based on user-centered design, our suggested methodology not only prevents patient’s data from leaking to TPA without depending on cryptographic algorithms, but can also avoid the use of additional free unpredictable supply that is impossible to fulfill on a daily basis. Also, we start to make our approach work with continuous changes. Our recommended scheme is both verifiably safe and essentially productive, as shown by the privacy analysis and test evaluations.
College students’ Network behavior Using data mining and feature analysis
Authors: Sravani Thatiparthi , Madala Srinivasa Rao , HeenaKauser Sk 
Published: December 2021

Abstract
Teachers may use advanced analytics to rapidly and correctly understand undergraduate behavior trends, especially when it comes to identifying undergraduate groupings that need to be focused on at a later time. This study uses data mining cluster analysis to analyze the constituent behavior of 3,245 undergraduates in a specific level ‘B’ institution’s college network. According to the data, there are four different undergraduate groups with different Web access features, with 350 participants using the accomplishments and other variables of their success have an influence on these students. As a result of this research, we were able to collect data on undergraduate college network activity, which may be used to aid in the development of academic advising management.