bluuebunny/crossref_metadata_2025_split huggingface dataset:
Study on performance and emission characteristics of split injection CRDi engine fueled with orange peel oil and diethyl ether
Authors: Periasamy Somasundaram , Chinnasamy Jegadheesan , Natarajan Jeyaprakash , Ravirajan Saravanan , Nagharajan Dhavaneeswaran 
Published: February 2021

Abstract
The constant increase in energy demand and the environmental issues due to higher utilisation of diesel fuel is frightening. The replacement of diesel fuel with biodiesel is the most viable solution to minimize the diesel fuel consumption and greenhouse gas emissions. The biodiesel with orange peel oil (OPO) and diethyl ether (DEE) can serve as a valuable alternative fuel, as OPO is naturally available with higher energy efficiency. The extracted orange peel oil characteristics gave its chemical and physical properties, which are suitable for using as additive for diesel fuel. The mixture is prepared with 30% DEE and 70 % of OPO to get B5 (950 ml Diesel + 35 ml OPO + 15 ml DEE) and B15 (850 ml Diesel + 105 ml OPO + 45 ml DEE) mixtures. In this study, a split injection CRDi engine is used to conduct performance and emission tests using the above three fuel options. The tests were conducted using the new blend for different engine operating conditions and the brake thermal efficiency of B5 mixture offers 0.6% to 2.3% higher values in comparison with diesel fuel.
Design and Development of Mobile AID for Muscular Dystrophy
Authors: Tony Thomas A , Mahesh Kumar K V , Thangarasu S K , Naveen Saravanan S 
Published: February 2021

Abstract
A group of muscle diseasesresulting in the increasing weakening and the breakdown ofskeletal muscles over time is called as muscular dystrophy. The disorders differ in parameters like which muscles are primarily affected, the degree of weakness of bones, how fast they become worse, and when the symptoms for this disorder begin. Many people will become unable to walk eventually. There are more than thirty specific typesof muscular dystrophy undernine main categories. The most common type among these is Duchenne muscular dystrophy (DMD). This is caused primarily due to the lack of a protein called Dystrophin and it is found in muscle fibre membrane of our body. Currently, there being no cure for it, somephysical, occupational, orthotic intervention (e.g., ankle-foot orthosis), speech, and respiratory therapies may tend in being helpful in terms of management. Being human they also love to travel alone and interested in satisfying their own needs which shows they need to live as a common man/woman than living in a situation where some people always crowd or assist around them in satisfying their needs. So, we decided to break the rules and allow them to move anywhere around their place and use the toilet during a nature call without anyone’s support by integrating the lifting mechanisms and the toilet provision in the wheel chair.
A cloud-based user recommender and e-governing system for public welfare
Authors: Kesavan Rupa , Meenakshi K , Vijayaraja L , Dhanasekar R , Dhilip Prasad P , Sim Stewart Itchiro E 
Published: February 2021

Abstract
Several problems exist in traditional analysis and design for e-government. The modern Era requires finding few solutions to dynamically facilitate the activities involved in administrative sectors of democratic regions. Individuals of a state or a central can be given an opportunity to actively participate in making decisions by placing their individual views on the democratic process for the better welfare. This paper is presented with the aim of developing a interactive system that adapts to dynamically updating the current policy recommendations, role of every crow sourcing committees, existing policy operational areas, beneficiaries, up-coming proposal plans of state and central regions for the welfare of rural and urban sectors. The framework facilities demand analysis, bringing many benefits to e-government planning, such as grasping emphasis immediately, affording to maximal benefit of democratic policies and plans. The Interactive system benefits mutually the individual as a Citizen and the administrator as the local parties of government body with efficient utilization, hence aiming at better development and implementation of goal plans that put forwards the Nation to step in to next degree of development by accomplishing the sustainable growth.
Smart Water Management towards Quality and Improvement using IoT
Authors: Revathi P , Mrunalini T , Niranjana M , Prithivi Raj C , Siva Prakash J , Sudharsan K 
Published: February 2021

Abstract
The raw water from rain water, ground water, bore well water, lakes, river, is filtered and fed into water tank using pre-filter and make it use for drinking purpose. In this paper, it has been mainly focused to measure and maintain the TDS value, pH value range between 30 to 400 ppm and neutral respectively in water quality improvement and also it is used to make it suitable for drinking water purpose. The whole process is monitored by using an open source Internet of Thing (IoT) application. It works via internet or via local area network. To measure TDS value and pH value in the water, required sensors are connected with node MCU controller, depending upon sensor output the antiscalant liquid is injected using submersible pump to maintain the essential parameters in the drinking water. Through the android device the information is send to the cloud which is used to monitoring the values. The values are automatically updated for every 15 seconds by IoT application by representing the date and time of occurrence of the value of TDS and pH of drinking water.
DESIGN AND FABRICATION OF IOT SWITCH WITH MANUAL OVERRIDE
Authors: Praveen Kumar S. , Srihariharan D. , Sai Harish Adithya K. M. , Hemachander R. 
Published: February 2021

Abstract
Today internet is the widest platform used by humans which connects people to people, but various researches have been carried out to connect machines to internet on a cloud platform. These are collectively called as Internet of Things (IoT). IoT helps to control and monitor the machines in factory, but later it is also used in home automation to connect household electrical devices like fans and lights. Each device will have their own control medium to access them and monitor them which makes the user, a tedious process to track them. There arises a need of, connecting all the devices and operating them in a common platform. Accessing the main supply of the appliances and turning ON/OFF that supply will be a suitable solution to control any range of applications. Hence, smart switch is becoming more popular now- a-days. But, most of the smart switches replace manual switching and goes for complete software-based switching. This makes the user to rely on the software/application all the time to control the device, even though the user is near the device. In order to solve these problems, in the proposed method a smart switch which follows the manual toggling action of conventional rocking switches to turn them ON/OFF manually and also provide access through remote applications to turn ON/OFF them through a mobile application.
A Survey of Machine Learning Techniques using for Image Classification in Home Security
Authors: Ganesh Babu R , Dhineshkumar K , Sharma Rohit , Krishnamoorthy R 
Published: February 2021

Abstract
Over the previous decade, creativity online has changed dramatically. Technology creativity has thus become a huge assist to protect our day-to-day lives. In this paper, introduce a powerful face-recognition of dependent security system. Specifically, set up this system to give verified customers access to a home. A further versatile learning strategy is used to prepare the classifier. Information about the planning is collected at first from interpersonal organizations. The classifier’s precision is increasingly increased as the client begins using the system. An amazing technique has been familiarized with how human interaction and web-based life boost the classifier model. When using a deep learning framework – Tensor Flow, reuse of the receiving device with various gadgets and applications would be anything but difficult.
A Nematic 5CB Liquid Crystal based Dual Band Microstrip Patch Antenna using Moth Flame Optimization
Authors: Srilekha G. , Pardhasaradhi P. , Srinivas G , Praveen N , Madhav B.T.P. , Rao M.C. , Venkateswara Rao M. 
Published: February 2021

Abstract
Microstrip patch antenna with different substrate materials which can operate in single and multiple resonating bands are useful for wireless applications. A 5CB nematic liquid crystal based microstrip antenna with dual band on a glass substrate having relative permittivity of 6.438 has been designed in this paper. Two glass substrates of 0.1mm thickness with 21x25mm2 and 19x19mm2sizes have been placed on each other, in between 0.005mm glass substrate has been placed to fill 5CB nematic liquid crystal. On the top of the substrate ‘I’ slotted rectangular patch has been placed; the dimensions of the patch have been calculated by utilizing Moth Flame Optimization (MFO) method. The proposed antenna is resonating at 1.8 GHz and 9.2 GHz frequencies with S11 as -27dB and -19.42dB, respectively. Simulated results of designed antenna with MFO algorithm are compared with Genetic Algorithm (GA).
Recommended System For Wellness Of Autistic Children Using Data Analytics and Machine Learning
Authors: Karre Kusumalatha , Rama Devi Y 
Published: February 2021

Abstract
Autism is a mental condition which hinders social and communication skills. It’s a lifelong disability which makes the child’s day to day life very difficult. But in most of the cases early intervention has helped the children to develop the skills which are needed to the fullest to overcome autism. As early the intervention, better the development of the child. Most of the research has been carried out to detect the autism using various machine learning algorithms which consider autistic diagnostic tools such as ADI-R, ADOS or CARS. Once autism is detected, different areas which need to be developed are considered and recommendations are given to the child. In this paper, a system is proposed which uses multi dimensional data collected from facp, DST and Diet to perform analytics using machine learning and provide recommendations to the child.
Blockchain technology using consensus mechanism for IoT-based e-healthcare system
Authors: Arul P , Renuka S 
Published: February 2021

Abstract
In healthcare systems IoT device has to give sensitive and private information about the patients, it should be maintained extremely confidential and personal. Most of the IoT-healthcare devices based on existing centralized server data management technology don’t give any guarantee of authenticity and security. Blockchain is a public tamperproof ledger that is decentralized network system in which transaction of data is distributed among the nodes. Blockchain with its consensus algorithm can solve problems by providing decentralized computation for IoT data. The combination of IoT and blockchain technologies with consensus algorithm can become a best choice of designing the secured distributed e-healthcare systems. This paper reviews the blockchain technology and the basic principle and characteristics of a consensus algorithm for IoT- based e- healthcare system.
LRFM model for customer purchase behaviour using K-Means algorithm
Authors: Jamunadevi C , Tamil Selvan S , Govindarajan M , Saravanan C , Janaki Raman B R 
Published: February 2021

Abstract
The COVID-19 pandemics have a major collision on every aspect of life, including how people shop for their requirements. As the pandemic has reshaped life as we know, it’s also initiated many trends – but the biggest of these trends may be online shopping. The shift toward online shopping was happening before the pandemic, but according to new statistics from IBM, the COIVD-19 has accelerated consumers shift toward online shopping by 5 years. The chief idea of the article is to inspect if the situation is approaching people to purchase things online and the continuation of shopping things online even after the end of pandemic. The information for the article has been gathered by circulating the survey on social networks. The questionnaire is comprised of 12 different questions, and 615 people responded to it. This work is based on LRFM (Length, Recency, Frequency, and Monetary) replica and separation of data based on the questionnaire using K-Means algorithm. Silhouette analysis helps to decide the extent of division among clusters. The results of the survey has a termination that people are fond of purchasing products online through the lockdown and people too agreed that the rate of online shopping will increase in the future when this pandemic is over.
Machine learning approach for detection of keratoconus
Authors: Shanthi S , Nirmaladevi K , Pyingkodi M , Dharanesh K , Gowthaman T , Harsavardan B 
Published: February 2021

Abstract
Keratoconus is a progressive eye disease and it should be detected in early stage, to avert probable refractive surgery that could develop ecstasies. In this the authors proposes a new computer aided diagnosis model based on Support Vector Machine (SVM) learning to detect the early stage of keratoconus using the available topographic, pachymetric and aberrometry parameters of patients with keratoconus, subclinical keratoconus and normal corneas. The proposed SVM produces 91.8% accuracy with 94.2% sensitivity, 97.5% specificity for classification of early keratoconus from normal; 100% accuracy with 100%, 100% of sensitivity and specificity respectively for classification of early keratoconus from subclinical keratoconus.
An empirical research on consumer online buying behaviour during the COVID-19 pandemic
Authors: Jamunadevi C , Deepa S , Kalaiselvi K T , Suguna R , Dharshini A 
Published: February 2021

AbstractThe extraordinary episode of the 2019 novel Corona-virus named as COVID-19 by the World Health Organization (WHO) has put various governments around the globe in a shaky position. The shortage of health care facilities to bear the COVID-19 has forced the countries to go with the hand of complete or partial lock down. According to the World Health Organization (WHO) report 32.6 million cases has been recorded as on 26 September 2020. Corona-virus have its major influence on consumer buying behaviour which is going to change the consumers’ future hopping habits. This article highlights the change in consumer behaviour from physical store to online shopping. The present study was conducted during the month of July- August 2020, where questionnaires’ are formed and data collected using Google forms. Analysis of the data is made through Simple percentage method, ANOVA test, Chi square test and ranking method. After analysis it found that the majority holding 21-30 age group of customers prefer shopping while free shipping and their cart behaviour is also analysed for the same.
Generative Adversarial Networks in Disease Gene Drug Relationships
Authors: Vijaya S. 
Published: February 2021

Abstract
The swift growth in the form of digital information stored in the biomedical databases in this digital era has activated a prototype shift in the models in the Deep learning approaches which have used in several contests in Machine Learning and in the domain of pattern recognition. Finding relationship between entities like genes, diseases, proteins and drugs is tedious task due the ambiguity in the terms used in biomedical domain. Treating cancer with the drug based on the gene that is associated with the disease increases the survival rate. Hence, the deep learning method “Generative Adversarial Networks” is proposed to find the relationship between Genes, Diseases and Drugs from biomedical abstracts in this work.
An Intelligent Framework for Traffic Management System Using Narrow Band-IoT
Authors: Rajaguru R , Mathankumar M , Balakumar A , Dinesh Kumar J R , Stonier Albert Alexander 
Published: February 2021

Abstract
Traffic management system is a key parameterfor highly efficient transportation system rather than depending on the speed of the vehicles and how smart it works. Police may not have all the dynamic data, which changes in a fraction of seconds, such as traffic due to accidents. The idea is to propose a system that can identify a truck in a road network and make decisions on clearing the traffic signals by getting results from the individual junction in a network. The system uses Narrow Band Internet of Things (NB-IoT) which is faster and energy-saving, and it sends signals to the particular traffic system based on the previous or the next traffic node. The Artificial Intelligence (AI) model will be biased independently. The system sends a message using radio waves from unused bandwidth. The main aim of the system is to make the passengers spend less time on traffic signals and save time as well as energy of the transportation system. It works based on getting traffic density on an individual traffic signal and the system decides which message should be open and which to close.
Optimal Design, Re-engineering and Testing of a 50:5A Current Transformer for Medium Voltage Industrial Requirements
Authors: Chandrasekar S , Pavudharani M , Priyadharshini J , Sakthi Muruganandam E , Yogesh S 
Published: February 2021

Abstract
The current transformer is one of the types of instrument transformer which is designed in such a manner so as to produce a current in its secondary circuit which in turn proportional to the current flowing through it’s primary circuit. It is one of the components that needs to be installed inside the electrical panel board in order to measure the current flow through each phase of the three phase system inside the panel. Usually these electrical panel boards were designed by electrical based industries. One of such industries which was in need of a 50:5 ratio current transformer had handed over the current transformer design and manufacturing as an industrial work to the authors. In this paper the authors deal with the optimal design and re-engineering and testing of the current transformer that is used in the measurement of current.
Review of internet of things: distributed power in smart grid
Authors: B M Nandish , Pushparajesh V 
Published: February 2021

Abstract
Emerging technologies in the field of power sector are Artificial Intelligence and Information Technology. Electrical network is very complex and Far-reaching, the data that coming from the generation, transmission or from the distribution is abundant and needs to be processed for better efficiency and reliability. To achieve higher efficiency power grids are incorporating newer technologies and are adapting. Internet of Thing (IOT) is a modernized technology that can be used to collect the data or to monitor the physical components under the radar of the grids. This paper deliberates the use of modern technology in the smart grids to improvise the reliability and working efficiency. The concept of Distributed generation and the utilization of IOT in such scenario is discussed in this paper.
FFNN BASED MPPT CONTROLLER FOR PEMFC POWERED NON-ISOLATED HIGH GAIN DC-DC CONVERTER WITH SPWM INVERTER FED BLDC MOTOR
Authors: Karthikeyan B. , Kalyanasundaram V. , Vidyasagar S. , Sundararaju K. , Palanisamy R. 
Published: February 2021

Abstract
A Non-Isolated High Gain DC-DC converter fed from 1.2kW PEMFC is designed to boost the fuel cell voltage. The Feed-forward Neural Network based MPPT controller algorithm is implemented to adjust the duty cycle of DC-DC converter in order make sure optimum power extraction from PEMFC whose result is compared with Fuzzy Logic Controller. The boosted DC voltage is inverteted to drive BLDC motor by three phase inverter. The inverter switches are triggered with switching pattern generated by SPWM technique according to the Hall sensor signals placed at stator of BLDC motor to find the position of rotor. The simulation anlysis has been carried out using MATLAB (R2017a)/Simulink platform and discussed the results.
Multilayer electromagnetic wave absorber by a dielectric material in direct to home system
Authors: Snega S , Narmadha K , Yuvashree R , Arunkumar M , Dhanasekar R , Vijayaraja L , Kesavan Rupa 
Published: February 2021

Abstract
The satellite is the one which plays a vital role in the medium of satellite dishes for television, communication, internet and most important role in military application. The solution for this problem occur in the satellite dish used for television is discussed here. Whenever the development is done by taking the technology as medium and smart innovative work are done, at last it has some disadvantage which finally occurs as a problem that is changes in meteorological conditions leads to disconnection of the signal. Although a renowned parabolic reflector is there, it gets shattered before reaching the receiver due to the cold rain weather condition. The method and material proposed here will be able to overcome the problem occurred.
Design of off-grid solar photovoltaic system using DC-DC topologies for BIUST classrooms
Authors: Tlhabologo B A , Molosiwa G , Ongadile O , Samikannu Ravi 
Published: February 2021

Abstract
The project is to Design and Develop an OFF-GRID solar photovoltaic System using DC-DC Topologies for BIUST classrooms light loads (lighting, projector, and computer). Narrowing this topic, focus is on harvesting solar energy using photovoltaic cells then boost the power using a DC-DC boost converter. This project consists of different subsystems, which are combined to have the solar system for classrooms light loads. These are Photovoltaic Solar Array, Maximum Power Point Tracking (MPPT), DC-DC boost converter and battery bank stores energy to be used when the sunrays are not efficient to supply the load. Lastly a DC-to-AC inverter is designed. The system is design is based on performed calculation to size each component to keep the system efficiency high. According to simulation of different DC-DC converters using Simulink, boost was the best converter to use looking at the output characteristics desired. Results from Proteus software simulation of the final circuit correspond with expectation from literature review. Furthermore, PVsyst software has been used to do the mathematical analysis of the designed model showing an estimated payback period of 2.6years whereas the output power for PVsyst model is 11.9 kW which the system produces given the design parameters calculated.
Augmentation of Low Voltage Ride through (LVRT) Capability using ANN based electric spring for a Grid-tied Wind Energy Conversion System
Authors: Udayakumar M.D. , Saradha Devi A. , Raja E. , Nazar Ali A , Stonier Albert Alexander 
Published: February 2021

Abstract
Electric Spring (ES) is an innovative approach for distributed voltage control (DVC) whereas at the same time accomplishing nominal demand-side management (DSM) technique for continuously varying renewable energy sources. In order to demonstrate the efficiency of ES when deployed in enormous quantities across the grid-connected power distribution system, it is important to build easy and reliable simulation models of ES that can be integrated into large-scale simulation studies of the power system. The ES study gap identification method defines the ES dynamic simulation methodology that is appropriate for the WECS grid-connected voltage and frequency control studies. The integration of WECS to the electric grid leads to many serious power quality problems. Low voltage ride through (LVRT) capability improvement is one of the important constraints in grid connected WECS. This articleexamines the enhancement of LVRT capability of Doubly Fed Induction Generator (DFIG) based grid connected WECS by usingES. The effectiveness of proposed Artificial Neural Network (ANN) based Electric spring controller is compared with existing PI controller using MATLAB/Simulink software. It is evident that the proposed controller nurtures the trustworthiness of WECS when integrated with existing electric power grid system.