bluuebunny/crossref_metadata_2025_split huggingface dataset:
Big Data Technology for Developing Learning Resources
Authors: Sharma Kuldeep , Mahesh T R , Bhuvana J 
Published: August 2021

Abstract
Endeavours for adopting network data greatly from social media allude to give the specific methods in extracting value from data space, for example, conversion, transaction, message and others, where structured information sources originate from big business assets information and unstructured information sources originate from video and audio. It very well may be accomplished to extend the way toward extracting value from social network for designing the information sources to satisfy the association objective. This paper means to uncover the method for approach of big data in extracting information esteem from information complexity including velocity and variety into volume. This investigation was led employing contents analysis by looking into certain literary works in chapters, books and peer-audited journals and procedures in creating prototype employing data analytics related from users, time analytics and topic. The discoveries uncover that big data rising technology with analytics procedure gives specific favourable circumstances to change the trend of data fitted into innovative atmosphere of OLR i.e. online learning resources to upgrade in building up learning resources. Both model and prototype information extraction value can be upgraded to encourage the learning atmosphere in supporting the implementations with convenience and ease. This investigation is relied upon to add to improve the outcomes and learning atmosphere with achievement and performance by upgrading the learning process development of students to give online resources in the higher education setting.
Convolutional Neural Network Using for Multi-Sensor 3D Object Detection
Authors: Sudhansu Gadug , Mohamed Zabeeulla A N , Nachappa M N 
Published: August 2021

Abstract
The purpose of this article is to detect 3D objects inside the independent vehicle with great accuracy. The method proposed a Multi-View 3D System (MV3D) framework which encodes the sparse 3d-point cloud with a compact multi-view image, using LIDAR satellite image and RGB pictures as inputs, and predicts 3D boundary boxes. The network comprises two sub-networks: one for creating 3D artifacts and one for multi-visual fusion functionality. Propose an autonomous 3D object tracking approach to manipulate sparse and dense knowledge about romanticizing and geometry in stereo images. The Stereo R-CNN strategy applies Faster R-CNNs to stereo inputs such that objects are simultaneously identified and linked in conservative and liberal images. Such charts were then combined and fed into a 3D proposal generator to generate accurate 3D proposals for vehicles. In the second step, the refining network extended the features of the proposal regions further and carried through the classification, regression of a 3D package box, and guidance estimates, to predict vehicle location and heading in 3D area and add additional branches after the stereo region Proposal Network (RPN).
Evaluation of Filtering Techniques in Channel Estimation for MIMO - OFDM Systems
Authors: Karthickmanoj R , Padmapriya J , Sasilatha T. , Aagash G 
Published: August 2021

AbstractNoise in a signal is an unwanted Distribution occurred which disrupts the original signalduring transmission, Depuration or conversion. Also noise may be random, with an unspecific mean or white noise with an independently interleaved distribution, zero mean by the processing algorithms. Performance degradation of Orthogonal Frequency Division Multiplexing system with Multiple Input and Multiple Output would have ensued due to the noise distribution in an original signal, so it is inevitable to reduce the unwanted noise distribution in an original signal to recover the original information which is sent at the transmitter. Various filtering techniques in channel estimation have been proposed in this literature to denoise a signal in Multiple Input Multiple Output – OFDM system effectively. The main intent of this survey is to provide the better insight of various denoising techniques in channel estimation to reduce unknown noise distributions in a signal with the tradeoff complexity in MIMO – OFDM systems.
Neural Network Based Weeding Robot For Crop And Weed Discrimination
Authors: Florance Mary M , Yogaraman D 
Published: August 2021

Abstract
Weeding is the most difficult process in the field of agriculture, which may consume more manpower, time and money. This paper is designed for detecting out weeds in-between crops and drilling them using blade attached at the end of robotic. Though this robot works autonomously, this does not require more manpower. It offers reduced working time and requires less installation cost. Insufficient labour, improper weeding, pandemic situation like Covid19 are some problems which can be avoided by this robot. This form of weeding is eco-friendly and does not affect the organic nature of the crop. It uses Convolution neural network(CNN) for detecting the image of weed from the crop.
Gate Bolt
Authors: Senthamil Selvi M. , Jansi Rani S. , Nisha A. , Sneka  , Sruthi C. 
Published: August 2021

Abstract
At current scenario, welfare and safety of children is one of the vital thing all need to be engrossed as many parents are leaving their child unaided in home in order to look their professions. The situation makes the intruders to get touch with unassisted child, this make many unwelcomed problems. To make over the above situation, this project would upkeep state of affairs to assist the parents who are in apprehension about child’s safety. A parent deeply impacts his child’s safety. This gets very tricky when both the parents are working. It reduces the amount of attention that your child gets, thereby affecting his psychological as well as behavioural aspects. An everyday home security level improved the security to our home with the help of AI based face recognition system. To create the door, unlock system by facial recognition uses the basic of camera facility and the network connection (internet). The doors be opened only when the face recognised by the system. This project helped to further improves the safety, security, automation control especially in the home. This system will restrict the entry of unauthenticated person and if so the new persons image captured by the system and the intimation sent to the admin person. The framework ought to likewise uphold the secret phrase opened framework.
Delay-Tolerant Sensor Network (DTN) Implementation in Cloud Computing
Authors: Dhabliya Dharmesh 
Published: August 2021

Abstract
In this study’s scheme, the objective is to employ the robot to implement the location estimation process for sensor nodes with which it interacts relative to the radio messages’ signal strengths, having received the signals from the sensor nodes. The implication is that the central purpose of the study lies in the elimination of the static sensor nodes’ processing constraints. Imperative to highlight is that the study’s mathematical contribution lies in the utilization of the REKF-based state estimator to analyze the localization problem. Deviating from Kalman Filter, it is worth noting that REKF exhibits computational efficiency and robustness. Indeed, the localization scheme is implemented on a hybrid network test bed.
IoT Based Control of Hybrid Energy Storage System for an Electric Vehicle using Super Capacitor and Battery
Authors: Balachander K , Amudha A , Mansoor Ali M 
Published: August 2021

Abstract
This main objective of this project is to control the hybrid energy storage system in order to increase the lifetime and performance of an electric vehicle battery source. This can be achieved by utilizing the powerful super capacitors in order to satisfy the peak power demand in an electric vehicle. When there is sudden raise in acceleration the peak power demand raises and hence the battery life gets reduced when there is sudden peak in discharge. In order to overcome this drawback, the super capacitor based auxiliary energy storage system comes into the role. We have used ARDUINO as a brain of this operation and it smartly identifies the excess power demand, cruise and normal mode of acceleration and rapidly switches between the battery storage and super capacitor storage accordingly in order to increase battery life time.
5G Network Security Issues, Challenges, Opportunities and Future Directions: A Survey
Authors: Humayun Mamoona , Hamid Bushra , Jhanjhi NZ , Suseendran G. , Talib M N 
Published: August 2021

Abstract
5G is expected to bring tremendous advancement in wireless cellular network by providing faster speed, high capacity and low latency. It has widely been adopted in various parts of the world and is expected to bring a noteworthy revolution in major industries and overall economies. Although 5G service providers are promising integrity, confidentiality and availability of data, still security is an important concern that needs to be addressed. This paper provides a detailed survey on 5G security by addressing 5G opportunities, common threats targeting 5G network along with their mitigation strategies, security services offered by 5G networks and 5G security challenges. We have also provided a case study to demonstrate the potentials of 5G. This survey will help 5G researchers, service providers and 5G users in getting quick awareness of 5G network.
Green Synthesis of Silver Nanoparticles Using Mukia Maderaspatana
Authors: Preetha N. , Padmavathi S. , Mahalakshmi B. 
Published: August 2021

Abstract
Nanoparticles are utilized in numerous business applications and it has been discovered that watery silver particles can be diminished by fluid exoact of plant parts to deliver exoemely stable silver nanoparticles in water. On this premise, silver nanoparticles (SNPs) were incorporated utilizing leaf aqueoi separate (LAE) of Mukiamaderaspatana. The acquired particles were broke down by UV-obvious spectrophotometry, checking electron microscopy (SEM), Fourier change infrared (FT-lR) spectroscopy to perceive the morphology of AgNPs. FTlR spectroscopic trials hax’e been performed to group potential bioreducing specialists present in the leaves of the plant.
Study on Darcy-Forchheimer Flow and MHD Boundary Layer Flow with Heat Transfer Characteristics of Williamson Nanofluid Over Curved Stretching Surface.
Authors: Sharma S 
Published: August 2021

AbstractPrinciple targets of this paper are to consider the Darcy-Forcheimer and magneto hydrodynamic limit layer stream with warmth and mass exchange of Williamson nanofluid over a bended extending surface. To create the stream, a non-straight bended extending surface is utilized. Likewise the capacities thermophoretic dispersion and irregular movement are created in the stream. The pertinent overseeing limit layer fractional differential conditions are changed into common differential conditions by utilizing existing comparability changes. These nonlinear coupled normal differential conditions, subject to the fitting limit conditions, are then addressed by utilizing bvp4c strategy. The impacts of the actual boundaries on the stream, heat move and nanoparticle fixation qualities of the issue are introduced through diagrams and are talked about in detail. The skin rubbing coefficient, neighborhood Nusselt number and Sherwood numbers are figured. In light of these plots the ends are given, and got results are tried for their exactness.
Hybrid Model for Pattern Discovery in Data Communication to Enhance Customer Relationship Management using Data Mining Techiques
Authors: Arivazhagan B , Sankara Subramanian R 
Published: August 2021

Abstract– Data Communication in customer oriented sector has significant information which is considered as a vital part in enhancing and improving customer base. Loyal customers in business sector are based on buying and selling of products or making use of services provided. Generally, the customers may switch on to variant enterpriser who affords best services with best price hence retaining them is a tedious task unless their communiaction data regarding service is analysed in periodic and to keep track of customer, the enterpriser should know the purchasing pattern and needs of loyal customersThe discovered pattern is also helps to afford proper discounts to the customers at the right time. This research paper experiments customer data in Telecommunication sector to discover useful and interesting patterns. There are so many data mining techniques put forward in revealing the pattern and this paper discusses all the possible mining techniques and evaluates an association rule mining with clustered data to create best rules. For clustering, Hierarchical agglomerative is used and FP-Growth algorithm is used for association rule mining. Both clustered data and association rules results regarding data communication are presented. The research work is implemented in weka tool and assessed with suitable evaluation metrics.
Power Generation using Hybrid Energy System for Domestic Purpose
Authors: Harinarayanan J. , Anusha Chindrupu , Mithra Ruba Shree R , Sheryl M 
Published: August 2021

Abstract
We all are aware that the world is precisely running towards a quest for a substitute energy source. Till today, the maximum power requirement is met with the help of fossil fuels. Anyways the estimates which were made recently have predicted that the usage of the fossil fuels like oil and coal might last only till 2030, and later we will have to switch over to the usage of more efficient sources and emerging technologies. According to current situation the further usage of oil and coal will be replenished and whole world will need to foster for renewable energy source which can satisfy the growing needs of the future generation. For the past few years solar and wind energy have already been trapped and are widely accepted as an alternative source of energy. But in this paper we have planned to concatenate the three outcomes i.e. heat, pressure and sound. Most of the times these three energies are considered as unwanted source of energy and they go unnoticed. With the help of Peltier module, Piezoelectric transducer and sound absorption unit the energies like heat, pressure and noise can be converted into electrical energy respectively. Piezoelectric plate transducer is capable of producing energy using the pressure put on the piezo electric plate. In this paper a footstep piezoelectric plate is used easy to incorporate and even effect cost wise. Peltier module is a thermoelectric device which has the capability of converting the thermal/heat energy into electricity. It primarily works based on the principle of Seeback effect. This device is built using 2 different semiconductor material like p-type and n-type. As the heat emerges and spreads through the material, charge carriers begin to cold side from hot side. The resultant voltage is proportional to the difference in temperature between the layers of the device. As long as there is a difference in temperature the material keeps generating the potential difference. The voltage produced by the entire Peltier module is function of time and the temperature difference. The voltage varies with the change in temperature gradient and time. The sound absorption unit uses sound as an input for producing electric energy, because lot of sound is wasted in our surrounding where in it can used as a source of energy. By using these non-conventional type of energy resources, the generation of power can be achieved with a minimal cost and it will also pave a way to the conservation of the conventional energy source for future needs. This energy thus generated is boosted and stabilized using a DC-DC chopper and later utilized to operate a DC load.
Computational Investigation of Optical, Thermal and Thermoelectric Properties of Cs3P compound
Authors: Jayalakshmi D S , Hrisheekesan T , Akshaya G , Hemanand D , Chembian W T , Arun Prakash P 
Published: August 2021

Abstract
Electronic, Thermal, Thermoelectric and Optical Properties of Cesium Phosphide Cs3P, are determined by means of Full-potential (FP) Linearized Augmented Plane Wave (LAPW) method using DFT (Density Functional Theory). Band structure, Density of States and Principle Optical constants of the compound were calculated. The computed Band gap and DoS (Density of States) histograms of the compound are agree well with the experimental studies and are similar to the compound used as reference which has been previously studied.
Segmentation and classification using image processing and supervising learning framework for mitosis detection in breast cancer mammographic images
Authors: Krithika P , Ramesh Sukruti , Satya Padigi Reddy , Deiva Preetha C A S 
Published: August 2021

Abstract
Detection of the area withholding the mitotic cell growth is a vital marker in breast cancer detection. This paper aims to fabricate an automatic Computer-Aided Detection (CAD) [2] model that helps to locate the region of mitotic cell growth and signify the type of breast cancer found: benign or malignant. Contrary to the legacy literature [1], which uses partially supervised learning models applied to histopathology images, we devise a model which involves a fully supervised convolution model applied to mammographic images. The model trained with image datasets: benign and malignant breast cancer images. This model exploits the MIAS database and datasets collected privately from hospitals, consisting of mammographic images available as samples for breast cancer detection. Applying image segmentation techniques to the datasets, we highlight the region of interest, and thereby using classification methodologies, we separate the results as benign or malignant. The developed model equips us to yield results with an accuracy of 97.96% on the dataset.
Design and Implementation of Human Stress Detection System: especially for Autistic children
Authors: Payani M , Raja K M , Saraan J , Srihari P 
Published: August 2021

Abstract
Stress can be recognized as a normal feeling when it is in its limit. If it sustains for more days it will surely lead to a number of diseases. A person should learn to handle stress in order that doesn’t affect him as well as his surroundings. Many people don’t realize the occurrence and reason of stress. The working condition of some people never gives any option of thinking mental strength (i.e., stress management). Children who are referred to be autistic will not be able to express their internal feelings which also reduce their confidence level. Hence a system which monitors, detects, and analyses the health parameters will really help as a supplement care taking unit. It consists of a pulse sensor, temperature and skin resistance detecting circuit. The former sensor detects the heart beat rate and temperature of the human body which helps in the stress detection. Skin resistance circuit makes use of skin property namely galvanic skin response to detect the stress levels. These sensor detected values were used to manipulate the stress level. The ThingSpeak cloud is accessed to store the data obtained. The data can be sent to the user through email automatically after the prescribed time. This report can be used for stress management and also for treatment purpose. The person will definitely realize the importance of stress management and hence the concerned person will have a look on the report.
Walk Assistance For Outwardly Challenged People
Authors: Rajkumar K , Thejaswini K , Subarna S , Yuvashri P 
Published: August 2021

Abstract
The blind’s competency is to navigate to a particular place and to commence their daily activities is of decisive importance for their prosperity. It is estimated about one billion people are blind out of 285 million people visually impaired of all ages, according to the statistics of World Health Organization. This work includes an affordable and more efficient navigation aid for the blind which provides artificial vision by providing knowledge about an environmental scenario of static and dynamic characteristics of objects around them. This system induces a smart cane with ultrasonic sensors placed to intimate the intermediaries to their acknowledgment through Bluetooth. ZIGBEE used in this project so as to met the sensor and control device communication standards for navigation for the blind with the smart cane via Google maps their destination.
Twitter Sentimental Analysis based on Ordinal Regression
Authors: Nennuri Rajashekar , Geetha Yadav M , Sai Vahini Y , Prabhas Goda Sairam , Rajashree V 
Published: August 2021

Abstract
For associations and people with a profound social, political, or monetary Sinterest in keeping up and fortifying their clout and notoriety, Twitter has become a goldmine. Sentiment analysis is the way toward characterizing and classifying the considerations and sentiments communicated in a source record. By performing this assessment investigation in a meticulous space, it is feasible to decide the force of area data on notion order. For feeling examination order, the proposed system utilizes the calculations Support Vector Regression (SVR), Decision Trees (DTs), and Random Forest (RF). The real execution of this structure depends on a twitter dataset unveiled by the NLTK corpora devices. The proposed approach will precisely identify ordinal relapse utilizing AI procedures.
Application of neural and bayesian networks in diesel engines under the flaw detection method
Authors: Prada Botia G C , Pabón León J A , Orjuela Abril M S 
Published: August 2021

Abstract
The identification of premature faults in Internal Combustion Engines has become determinant to guarantee suitable operation. Therefore, this study focuses on the implementation of fault diagnostic methodology by using advanced algorithms such as Back Propagation neural networks and Bayesian networks. Results indicated that the proposed methodology serves as a robust tool to identify different fault conditions in a wide operational spectrum with an reliability of nearly 73%. Moreover, the Backpropagation network diagnostic methodology presented an reliability of 18%, which is 3% higher than Bayesian networks. Overall, the implemented methodology counterbalanced interference conditions and noise signals while providing versatility to operate for different types of engines. In conclusion, this study can be extrapolated to different fields of physics to assist in identifying flaws in experimental test benches.
Study of the modified Weibull function to analyze reliability in engineering components that fail and are repairable
Authors: Espinel-Blanco E , Flórez-Solano E , Arévalo-Rueda J 
Published: August 2021

Abstract
An engineering component is physically inoperative when it fails or has conditions that prevent it from operating and has a functional failure. The useful or operating times and the non-operating or downtimes are collected to determine the reliability or the probability of operation of the component during a period. The use of distributions is the most accepted method for determining component reliability. Among the main distributions used are the exponential, Log Normal, Weibull, etc. The Weibull distribution is widely used to estimate the reliability of a component, understood as the physical capacity of the element to function according to operating parameters. A study of three models based on Weibull modifications was conducted to determine the reliability of repairable components subject to maintenance activities. Two models represent the modified Weibull function with two parameters and an additional model that represents the Weibull function transmuted with failure rate function that fits the Davies curve. The characteristics, the physical interpretation, the applications, and the feasibility of using each model in analysis of reliability in elements and repairable in engineering are presented.