bluuebunny/crossref_metadata_2025_split huggingface dataset:
Learning Design of STEM Education Through Workshop Training for Thai Teachers
Authors: Madahae S , Pisapak P , Thanyasirikul C 
Published: May 2021

Abstract
Learning in the 21st century is a learning that focuses on developing higher-order thinking skills and integrating sciences into a daily life. Therefore, teachers have an essential role in designing learning activities in order to encourage learners to improve problem-solving, creativities and collaborative skills. STEM education is a curriculum based on the idea of educating students in four specific disciplines including science, technology, engineering, and mathematics. These disciplines were integrated into a daily life through an engineering design process consists of 6 steps as follows: (1) Problem Identification, (2) Related Information Search, (3) Solution Design, (4) Planning and Development, (5) Testing, Evaluation and Design Improvement, and (6) Presentation. This paper is a presents teachers’ learning activities design through workshops including lecturing, Bionic hand, Floating Restaurant and hand-on activities which are developed based on STEM education to promote as a professional teacher and to respond the learning in the 21st century.
Power Generation Using Sound by Piezo Electric Material
Authors: Chaithanya D J , Anitha S , Ramya B , Aisiri A P 
Published: May 2021

Abstract
Pollution is a major problem all over the world. According to the energy conservation statement law states that energy cannot be created or destroyed but can be converted from one form to another. As it relates to nature, the sudden increase in urban and industrial growth has been completed with potentially hazardous waste. Sound is the electrical energy of the machine and can be converted into electrical energy through many provocative methods including heating using piezoelectric material and diaphragm. Other sounds are not preventable such as road noise, market noise, industry, train stations etc. and those unnecessary noises can be used to generate electricity. In this way we can reduce the use of piezoelectric power and energy generated by chemical materials where it is converted directly from energy to electrical energy. The widespread use of this space is to focus on how we can increase the electrical performance generated by the conversion of sound energy from non-renewable sources. When sound vibrations are in the diaphragm and are compressed and hard to convert into electrical energy.
Biometric based Fingerprint Verification System for ATM machines
Authors: Sangeetha T , Kumaraguru M , Akshay S , Kanishka M 
Published: May 2021

Abstract
In this modern world, almost everyone uses ATM machines which allow people to transfer and withdraw cash. This study is based on executing a fingerprint method in the ATM System. We chose this field to improve safety and security for people to make the transaction easier. The fingerprints are unique for each person. There is no insecurity of losing an ATM card and no requirement to carry an ATM card with you every time. On comparison of different technologies for ATM security, the fingerprint technology operates better and safer than others. These reasons make this mechanism an effortless and secure way of transaction and also maintains a coherent ambience with users and ATM machines. This is the most latest technology in electronic cash transactions.
Intelligent Driving detection with Health Monitoring and Accident detection System using IOT
Authors: Malathi M , Pavithra S , Preakshanashree S , Praveen Kumar S 
Published: May 2021

Abstract
Accidents caused because of intoxicated drive are expanding massively in this advanced world. To forestall mishaps adequately the proposed framework can be actualized. In this structure, we screen the level of alcohol usage and heart beat rate. In the event that the chauffeur is related to intoxicated journey, at that point the transport medium start framework will break off which creates the inebriated chauffeur incapable to locomote the transport medium bringing about mishap avoidance. In addition to this, if there are any atypical alternates in heart beat rate, at that point the momentum status of the chauffeur is sent to their bosom companions and relatives using iot. Since pragmatic execution in transport medium is past the extent of this task, we are actualizing the proposed framework with a dc appliance.
Electromyography in MachineLearning
Authors: Kiruthika K , Nishanthi S , Rahul A , Senathipathi K 
Published: May 2021

Abstract
This project is based on the utilization of AI and conclusion of electromyographic data. The information cleaning has been led dependent on the particular planned incorporation standard. Two informational collections have been organized which contains 575 facial engine nerve conduction and 233 hearable brain stem reaction reports. And afterward, four AI calculations including irregular timberland, direct relapse, uphold vector machine and strategic relapse have been appropriated to the informational collections. The exhibition correlations of precision and review rate among various calculations demonstrate that the irregular backwoods calculation has the ideal presentation over the other two collections. The correlation has been done for every calculation and the deviation normalization certainly affects the exactness outcome. Subsequently, the irregular wood is demonstrated to be an ideal calculation for PC supported finding frameworks. Besides, it merits referencing that the component selection arranged by significance can encourage clinical interpretation in analysis and symptomatic appraisal.
Design of FIR Filter Using Adaptive LMS Algorithm for Energy Efficient Application
Authors: Shanmugam Yamini , Subbiya A , Sudhakar M , Harsha Visali D 
Published: May 2021

Abstract
This paper presents the LMS (Least Mean Square) sub-channel. Minor square calculations have been used in many DSP programs to address the signal and are intended to create channel coefficients based on the adjusted signal. The proposed strategy reduces energy and regional consumption due to the modification of locally produced loads in terms of revised yields and previous loads. The cargo area decided to use the LMS calculation. Suggested production was completed using Modalism, a coded structure using Verilog HDL and compiled by Xilinx Vivado. Power is determined by using the Xilinx power tester with a focus on FPGA. The significant results of the proposed framework have improved the region and capacity compared to the standard FIR channel.
A Multifunctional RFID enabled Shopping Tramcar
Authors: Dhivyaa M , Brindha C , Haritha T , Gokula Kannan S , Gunanandhini S 
Published: May 2021

Abstract
In the diligent world with full of time restraints people run behind time. In order to save time and labor graft, we have proposed a multifunctional shopping tramcar to avoid queues in the super-market and shopping malls. The core intent of this project is to develop a robust tool with high efficiency, minimal cost and an accustomated structure for the ease of customers and retailers. The system works with the integration of 7 modules. Firstly, develop a login credentials for each customer to connect the cart with the main server through a website based login and set the budget, if it crosses the limit it notifies the customer. The products are scanned via RFID scanner. Besides, this system is embedded with a technique which intimates the product spot when searched. It also has the anti-theft mechanism feature, enabling automatic bill display and automatic payment. The sales rate could also be predicted to drop down the work of a retailer.
Intelligent Mask Detection Using Deep Learning Techniques
Authors: Anantha Prabha P , Karthikeyan G , Kuttralanathan K , Manoj Venkatesun M 
Published: May 2021

Abstract
Owing to the corona pandemic, the government has insisted on wearing a safety mask and maintaining 6 feet distance to get rid of CoronaVirus. The detection of people with or without masks is a challenge due to the impact of Covid pandemic. There are some models / systems which really reduce the manpower to notify the people. The existing system runs on the model: Yolov3, V G G, for face detection and MobileNetv2 for face recognition, object detection, and semantic segmentation inorder to detect the people with and without masks. The proposed system holds an approach of detecting human’s faces and classifying them into people with and without masks which has been done using image processing and deep learning and our project runs u.3nder a model called Faster RCNN. Moreover, Faster R-CNN is more accurate while other models are faster. Being effective is not important but being efficient is way more important.
Hyperspectral Image Classification Using Ensemble Transfer Learning
Authors: Murugan K R Senthil , Kishore G , Inam S Mohammed , Karthikeyan K 
Published: May 2021

Abstract
Today there is colossal advancement in virtual age that has achieved the improvement of various technology without trouble using contraptions and procedures specifically with in the side the fields of interchanges and measurements change to an allencompassing distance. The transmission of insights within the state of reports, pictures, voice and so on is presently available to all components of the general public and the contributions are minimal effort to a greater assortment of individuals. A basic factor is insights Compression and recovery and for that to be checked Image Compression and recovery, as pictures shape a greater a piece of measurements being traded over the net through long range informal communication and informing web locales and applications wherever on the planet. Among the entirety of the various sorts of insights pictures and films address the bulkiest measurements. Consequently, need for compacting the photo archives is a basic factor in insights correspondence.
Analysis on Multi Modal Transportation System Using Spatial Domain Inverse
Authors: Sandhya G , Suvetha S , Swathi S , Shwetha R 
Published: May 2021

Abstract
Transportation Recommendation is one of the navigation application for map plotting. Earlier travel guidelines are unsatisfactory for consumers, provided that only one method of transport is required to consider their recommendations (e.g. unimodal, taxes, taxis, cycles), and that conditions are generally ignored. The proposed work suggest Hydra, a multi-task, highly-learned, multi-modal transport scheme that adapts to different contextual situations (i.e. delivery and weather close-up point of interest). This uses current city transport motorized routes and big data to build a two-level infrastructure. Fresh, two-stage routing approaches can be designed using regular and multimodal and multidisciplinary routing information as well as more diverse route combinations (E.g., taxi/bicycle). Inter urban data, modes of mobility preferences, vehicle urban OD patterns, and individual profiles of latent users are collected as part of the innovation mix. With the provision of spatial reverse, the overall framework support the architecture ideas and provide better visual representation.
Facial Emotion Recognition Using Deep Learning
Authors: Vimal K.U. , Sandij S. K. , Yogesh M. , Soundarya S. 
Published: May 2021

Abstract
Facial emotion recognition (FER), because of its significant academic and business potential, is an important subject in the fields of computer vision and artificial intelligence. The purpose of this project is to develop an emotion detection pipeline using video frames. In particular, we detect and analyse the faces of the video through deep neural networks for the recognition of emotions. We use a CNN and an RNN based on documents submitted in the Wild Challenge for emotional recognition. An input video is divided into small segments. We will detect, crop and align faces for each segment. This gives an image sequence. A CNN will extract relevant features in the sequence for each image. These features will be sequentially feed to an RNN that encodes emotional movement and facial expressions. The entire process is carried out as a Python.
High Step-Up Super - Lift DC-DC Converter with Enhanced Response
Authors: Suguna R , Rani R , Aiswar S , Gnana Moorthy C , Mukesh E 
Published: May 2021

Abstract
This exertion mainly deals with the design, analysis and simulation of open loop and close loop super lift converter with PI (proportional Integral) and FOPID (Fractional Order Proportional Integral Derivative) controllers. The objectives of this system is to reduce ripple in output of High Step-Up Super –Lift DC-DC converter and to regulate yield voltage of High Step-Up Super –Lift DC-DC converter using PI/FOPID controller. The upshots are contrasted in terms of Settling time and steady state error. FOPID controlled closed loop super lift converter showed the superior performance.
A smart AIS based portable wireless electric charging vehicles
Authors: Rani K S , Suguna R , Kumar R Senthil , raj C P Harish , Ram P Sri , Haran V Hari 
Published: May 2021

Abstract
As the production of electric vehicle has scaled up in the recent years in order to meet the objective of lowering the carbon footprint and eco-friendly transportation. The raise in the production of electric vehicles in accordance with hike in the price of petroleum and diesel has shifted the huge market share of the automobile industry from ICE engines to the battery powered engines. The shift in turn pushes the demand for installation of charging stations for electric vehicles at most locations. But the installation of such EV charging base stations requires high capital and sophisticated spatial infrastructure in densely populated area. Therefore, the paper proposes the AIS based mobile wireless charging system for electric vehicles which is cost effective and reliable. The system is best suited for densely populated areas, parking arenas at theatres, malls, parks etc., The Wireless Sensor Network is implemented to effectuate adaptive intelligent system, therefore leading to better accuracy and modularity.
Advanced Deep Learning Model for Future Forecasting of COVID-19
Authors: Lavanya  , Suganya R , Kanmani R. , Godwin Joyal S. 
Published: May 2021

Abstract
The roll out of corona virus (COVID-19) in the entire every country has put the mankind in danger. The assets of the absolute biggest economies are worried because of the enormous infectivity and contagiousness of this sickness. The capacity of machine learning models to conjecture the quantity and number of impending peoples influenced by corona virus which is by and by took as a possible danger for humankind. Specifically, Three layer of determining models, least outright shrinkage and choice administrator (LASSO) Support vector Machine – deep learning have been utilized in this investigation to estimate the undermining components of corona virus. Minimum Three kinds of expectations are proposed by every one of the systems, like the quantity of recently tainted reports, the quantity of passing’s, and the quantity of recuperations But in the can’t foresee the exact outcome for the patients. To defeat the issue, Proposed strategy utilizing the long Short-term Integrated Average (LSTIA) foresee the quantity of COVID-19 cases in next 30 days ahead and impact of preventive estimates like social segregation and lockdown on the Roll out of corona virus.
An Advanced Inductively Coupled Wireless Charging System For Electric Vehicle Applications
Authors: Elakya A , Abitha Shree K J , Ahil D , Bhobalan V , Elamano P 
Published: May 2021

Abstract
Any day today, the globe transitions to electrified transportation, reducing non-renewable fossil fuel pollutant emissions. Electromagnetic energy is transferred from the power source to the electrical charge without interconnection wires and the operation is carried out in every device. Electric cars are seen in the potential mobility area to be substitutions for the vehicles propelled by oil fueled internal combustion engine. In this project wireless charging technologies are examined using the inductive coupling approach. Numerous factors, including magnetic flow, inductance of the resonant bob, determine the performance of wireless power transfer and mutual inductance. The paper focuses in particular on static (stationary) charge, while dynamic loading (loading during driving) involves a dramatically different method. The Multi-Load method is modelled and the efficiency expression for each charge is determined with a different resonant frequency.
A Fast and Accurate Face Recognition Security System
Authors: Sruthi M S , Sarath S , Sathish R , Shanthosh S 
Published: May 2021

Abstract
Using facial recognition technology, provide the best security system with alerts for smart devices such as laptops and PCs. The design descriptions of the various modules involved in automatic face recognition are presented in this paper: face detection, face identification, and face verification. Also we’re visiting further process the image captured by CV to test whether the person is allowed or unauthorized to access the laptop or PC using openCV and native Binary Pattern Histogram (BPH) Algorithm. The LBPH algorithm is also a simple solution to the problem of face recognition, since it can identify both the front and side faces. A updated LBPH algorithm assisted pixel neighbourhood grey median (MLBPH) is proposed to solve this problem. After detection, the image is verified and allows only the user to access the laptop or PC if he/she’s authorized. And if not, an e-mail or message is pushed to the respective person to alert that somebody else is using his/her laptop by enhance the privacy.
Pollution Based Traffic Control System using IoT
Authors: Jaishankar B , bharathi M Dhivya , Harshavarthini G , Bharanidharan S , Harish S 
Published: May 2021

Abstract
With the rise in vehicle use, the amount of emissions at road intersections has raised, causing harm to those who are connected directly to it. It is proposed to control emissions using the Internet of Things (IoT) over stoplights, the ventilation levels of vehicles, and also the consistency of living air. The Internet of Things (IoT) carries out signals. A sensing element and a temperature probe are used in this prototype system. Carbon dioxide, greenhouse gases, and other toxic gases are identified by a sensor. In the air, carbon dioxide, dust, acid, and moisture are present. This analysis is accurate, distributed to the microcontroller on a daily basis and published to the web browser. The Wi-Fi module is a piece of hardware that allows to connect to the internet. On this basis the ON/OFF road markings modify the timing thresholds automatically. At traffic lights, this suggested technique degree of control emissions and climate.
Design of Digitally Controlled Battery Charging System Using DC-DC Converter
Authors: Saravanan S , Kumar R Senthil , Darshini K , Apurva G , Akassnidi K , Abhinayah R S 
Published: May 2021

Abstract
This initiative proposes a new battery charging device. The fundamental concept is to keep this project up-to-date by restricting charge time. The new constant loading technique is proposed and it has a digitally operated loader. Also, the adapter transfers control mode to continuous voltage charging with the battery voltage increasing to the default voltage mark. For battery charging applications, a digitally controlled charger is developed and introduced. A digitally controlled charger for battery charging applications is developed and introduced. The operation of the loader is subject to the proposed software control system. The closed-loop PID control also guarantees optimum electricity voltage. Three stages are used with the digitally controlled charger. The first step is to change the electric volume of 50 Hz to the DC volume with an appropriate power factor. The second phase is the DC-DC fly-back converter, changing the battery to its level and generating galvanic insulation. Step 3 uses digital power to keep the current and voltage stable. The project’s key aim is to maintain a steady voltage and current. The simulation is performed using Simulink with the MATLAB file Experimental findings show design and execution efficiency.
IoT Based Smart Fertilizer Management System
Authors: Jagadesh T , Sangeetha K , Sarvinprabhu R , Jagadesh R , Varshinee D 
Published: May 2021

Abstract
Agriculture is the backbone of the India and villages are the life lines for the growth of India. In our country, over 72% of individuals rely on cultivating which is 33% of the populace puts resources into cultivating. In this manner, the difficulties and issues concerning horticulture should be engaged to frustrate the nation development. The only one solution recommended to this issue is modernizing agriculture using smart technologies. In agriculture, irrigation and fertilizer supply are the two important processes which support crop production. The Conventional water system techniques include a ton of time and exertion in cultivating. A Sensor-based computerized water system framework with manure tank gives a promising answer for oversee rural action. This exploration article gives an immense report on the water system framework and in savvy horticulture.
Predicting heart disease using hybrid machine learning model
Authors: Renugadevi G , Asha Priya G , Dhivyaa Sankari B , Gowthamani R 
Published: May 2021

Abstract
Multiple Chronic disease are available especially Heart disease is the foremost reasons of death in modern world. Machine learning (ML) is useful for making conclusions and predictions based on a huge volume of data formed by the healthcare industry. The proposed approach uses machine learning techniques to find heart disease in this study. The prediction model, which employs classification techniques, is based on the Cleveland heart dataset. The Random Forest and Decision Tree machine learning techniques are used. This model for heart ailment with hybrid methodology has an accuracy level of 88.7%, according to experimental study. The boundary is determined as an input parameter from the user to predict heart disease using a Decision Tree method and Random Forest hybrid methodology.
Design and analysis of half-mode SIW antenna for home automation in IoT
Authors: Cowsigan S P , Renuka K , Shobika K , Swathi S 
Published: May 2021

Abstract
Substrate Integrated Waveguide (SIW) technology implemented antenna for home automation in IoT is presented in this paper. SIW exhibits a low copper loss, reduce surface waves, low radiation loss and low dielectric loss property. In this paper the rectangular waveguide has been designed, simulated, and fabricated to operate in 5 – 15 GHz frequency range. The important performance characteristics of antenna are simulated and measured. The rectangular waveguide has two parallel metallic cylinders consisting of via holes in which we can prevent the entering of unwanted radiations.
Six by Two Degrees of Wikipedia using BFS Algorithm
Authors: Jitendran K , Akash S , Aswin N , Rajesh Kumar T 
Published: May 2021

Abstract
SixbyTwo Degrees of Wikipedia is a concept that is built on the idea of Six Degrees of Separation, where articles can be connected within six steps. This theory motivated the invention of online communities, after succeeding in the real world. The above concept has been visualized for connecting two Wikipedia articles with a minimum number of articles connecting them, by using a modified BFS algorithm. This paper is helpful for students and researchers, for their research. The graph approach formulates the theory and evaluates the minimum number of links between any two given articles. This approach provides much faster results than other algorithms and the traditional BFS algorithm.