bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effect of Addition of Magnesium and Zinc to Obtain Optimal Mechanical Properties of Al-Mg-Zn Alloy
Authors: Mottar Al-Masoudy Murtadha Mohsen , Abbud Luay Hashem , Al-Jubouri Haidar A.H. , Sabri Zainab Amer 
Published: February 2021

Abstract
Many uses of aluminum led the researchers to develop this field by changing the target bullion to obtain alloys suitable for all specialties and possibilities. Adding some metals to aluminum leads to a change in properties, whether mechanical or physical, but in our research we target the mechanical properties, adding magnesium and zinc are in equal proportions (5%Mg-5%Zn, 10%Mg-10Zn). We offer this alloy to some tests such as hardness test, electrical conductivity test, compression test and Microstructure examination test. We compare the properties obtained with each other and with the basic properties of pure basic metal according to international standards.
Railway track tracer system for creature detection
Authors: Deepa M , Raji C G , Ajina VA , Ashla  , Azra Afsal , Susanna George 
Published: February 2021

Abstract
Railway Track Tracer System for creature detection is a system for detecting creatures on the railway tracks. This system will help to avoid many accidents that occur on rails. This system mainly focuses on some areas where creatures are always seen on the railway tracks. In some areas, elephants are crossing the railway tracks frequently. This system frequently monitors the railway tracks using a camera, so that the presence of creatures can be easily identified and then necessary actions can be taken to prevent accidents. The system includes a camera, train status system and an application for alert. The camera captures the images on the track at each interval of time and then through image processing the captured image will be recognized. If an object is identified on the track, then immediately an alert message will be sent to the nearby control room and loco-pilot. This system will be helpful for the society to prevent accidents due to creatures on the railway tracks.
GIS Study on Impact of Urbanisation in Perundurai on Ground Water Quality
Authors: Santhoshkumaar K , Muralimohan N , Ponkalidass K , Naveenkumar S , Nirmal K 
Published: February 2021

Abstract
Groundwater quality includes the physical, chemical, and biological qualities of well water. Temperature, turbidity, color, taste, and odor structure the list of physical water quality parameters. Since most well water is colorless, odorless, and while not specific style, we tend to are generally most involved with its chemical and biological qualities. though spring water or groundwater product are usually oversubscribed as “pure,” their water quality is totally different from that of pure water. The current work is geared towards assessing the water quality index (WQI) for the groundwater of Perundurai taluk and the tested parameter are mapped with the help of GIS. This has been decided by using aggregation groundwater samples and subjecting the samples to a complete chemical science analysis and to produce groundwater exceptional map of Perundurai Taluk using GIS.
Design and Analysis of Bumper Beam and Energy Absorbers by Using Composite Materials
Authors: Chinnasamy Jegadheesan , Periasamy Somasundaram , Chinnasamy Vivekanandhan , Prathip Kumar H. , Hariharan S. , Diwakar A. , Piruthiviraj B. 
Published: February 2021

Abstract
At present the production of automobile is in increasing rate especially India which is one of the largest producer and consumer of automobile. India uses wide variety of automobile like bus, car, van, truck and heavy vehicles. But India have a poor road quality and the driving facilities are less which results in severe road accident. This results in severe collisions of vehicles and it cause damage to both vehicle and passengers. Bumper is one of the key factor which helps in avoiding damage to vehicle and passengers present inside the vehicle. Thus all vehicles will have bumper for safety purpose. The bumpers are made of different type of materials to ensure safety of the passengers and to reduce the weight of the vehicle. The production of bumper in composite material results in increased safety during collision and it is cheaper and reduces the weight of vehicle. The cross-section of beam, energy absorber and its materials is designed and analyzed, with referring to the result safe and strong bumper system is discussed. When compared to current bumper, the composite bumper with energy absorber results in greater shock absorption and increased strength which increase the overall effectiveness of the bumper and its function.
Optimization of mechanical properties of ER-4043 specimens fabricated by WAAM process through Grey Relational Analysis
Authors: Sirisha Bhadrakali A. , Narayana K. L , Ram Prabhu T , Pratapa Reddy Y. 
Published: February 2021

Abstract
Wire Arc Additive Manufacturing (WAAM) is the process of used to fabricate material samples by deposition of material which is in wire form at high temperature ER-4043 Aluminium wire is deposited on substrate steel plate and predicted the properties by following Taguchi orthogonal Array. It reduces the complexity occurs by conventional process in fabricating a large size, complex shape components.
In the present investigation, the optimized multi-responses by Orthogonal Array (OA) which are strength and hardness values obtained during WAAM process for nine samples are evaluated to presage the influence of process parameters through Grey Relational Analysis (GRA) followed by Taguchi method.
A Detailed Survey on Improved Groundnut Harvest Automation System Using Wireless Sensor Network Technologies
Authors: Maneendhar R , Usha M 
Published: February 2021

Abstract
This paper analyses the wireless sensor network technologies on how to use in agricultural crop harvesting and highly productive yielding applications. Wireless sensor networks (WSN) monitoring the crop growth ubiquitous manner and sending crop growth report to the agricultural university administrator system. This survey paper makes a comparison between wealthy crop growth databases to actual crop cultivation reports. The main objective and motivation of this survey paper are tremendous changes are needed in the field of agriculture. Finally, they will give well-optimized suggestion to the farmers such that fertilizer recommendations, managing and controlling crop diseases, suitable irrigation system for crop cultivation, which is all the methodologies are helping to improve the yield of crops.
Wheeled wall climbing robot with suction chamber: A study on forces and moments for stability
Authors: Eswaramoorthy Sathish , Poovathy John Florence Gnana 
Published: February 2021

Abstract
Wall climbing robots (WCRs) are those that have the capacity to move against gravity and reach out to places where it is difficult for human access. For example, cleaning the inner surfaces of hot boilers in industries, painting highly raised buildings etc. In order to carry out these works, the WCRs must move over rough vertical walls. It is possible that, the WCR might tip over due to the uneven nature of the wall. The forces and moments acting upon the WCR while climbing a vertical wall have huge impact over the stability. Apart from rough surfaces, the WCRs might encounter few obstacles. The forces and magnitudes must aid the WCRs surpass these obstacles as well as rough surfaces and climb over the wall and ceiling. This paper studies the various forces and moments acting on the WCRs while climbing a vertical wall. Mathematical insight about the changes in forces and moments to maintain stability for various cases such as WCRs with payload, with two or more suction chambers, with many suction chambers with payload are discussed in detail.
Frequency sextupling millimeter wave generation by using lithium niobate mach zehnder modulator without an optical amplifier
Authors: Anand Prem P K , Pranit Jeba Samuel C , Nagaraj S , Subhashree G R , Albert Alexander S 
Published: February 2021

Abstract
The millimeter wave (mmw) based optical networks have been considered as the most promising solution to increase the capacity, coverage, bandwidth and decreasing cost for next generation access networks. The optical fiber technology utilizing mmw band is an attractive way to provide higher signal bandwidth and overcome congestion. In the present era the frequency having less bandwidth is used in the communication technology which increases the time delay. The proposed scheme is used to generate mmw with an applied voltage of 7 V for a distance of 50 km and data rate of 6 Gbps is achieved by using a Lithium niobate Modulator without an optical amplifier and filter. The carrier suppression scheme used in the LiNbO3 modulator act as a optical filter so that the complexity of the system is reduced. As the modulator helps to increase the frequency of the input signal to achieve a long distance transmission through an single mode optical fiber the number of optical amplifiers can also be reduced. To verify the robustness of the setup the visualizers are used which ensure the data quality.
Experimental Investigation for the usage of Diesel - Jatropha – Rice bran Biodiesel Mixture Blends in Four Stroke Diesel Engine
Authors: Karthi Vinith K S , Soundar A , Mahalingam S , Sujai S , Guru Prasad P K 
Published: February 2021

Abstract
In last few decades, the demand of fossil fuel increases due to the enormous increases in vehicle population. There is a shortage of crude oil supply due to the excess need of fossil fuel. This urges the researchers to switch to renewable resources, like biofuels. Biodiesels can be produced successfully from plants such as palm, jatropha, rapeseed, rice bran, soyabean, corn etc. The use of biodiesel will considerably reduce the emissions also and thus increases the engine performance. The oil is converted to biodiesel with the help of trans-esterification process. The properties, emission characteristics and performance for the Compression Ignition (CI) of the fuel process are examined for biodiesel which is blended with two oils (rice bran and Jatropha oil blend mixture) by using this experimental study. The results indicate that the calorific value forthe dual blends of biodiesel decreases with an increase in biodiesel concentration in the blends of diesel-biodiesel mixture. It is found that the brake thermal efficiency is lower for biodiesel blends. For higher ratio of blends, biodiesel blends givelower HC and NOx emissions.
Optimizing Wireless Multimedia Sensor Networks Path Selection using Resource Levelling Technique in Transmitting Endoscopy Biomedical data
Authors: Vanitha C.N. , Malathy S 
Published: February 2021

Abstract
The urge to transmit especially biomedical data rapidly is essential to save human life. Every user demands for high speed communication with no delay. But the network suffers from huge delay which degrades the performance of the network and it also dissatisfies the user expectation. To meet the user needs, the proposed work mainly focuses on increasing the speed and minimizing the delay in communication using Internet applied in Things (IoT) and Wireless Multimedia Sensor Networks. It can be achieved by avoiding over allocation of resources in the network i.e., resource level balancing and planning the transmission. These two have greater impact in upgrading the performance of network. This paper introduces a unique methodology for Wireless Multimedia Sensor Networks and end-device assisted system. The transmission time can reduced by using the concept of probability estimation for crashing the interpretative path. It extends the battery level of the motes by enhancing the pace and minimizing the energy level during transmission process. The Crashing Interpretative path protocol is simulated against other literature method. The simulation results shows that the CCP provides better efficiency in terms of transmission time, the lifetime of sensors for biomedical data transmission. This methodology is greatly helpful to save precious human life.
Mitigating DoS attacks in IoT using Supervised and Unsupervised Algorithms – A Survey
Authors: Gopal S.B. , Poongodi C. , Nanthiya D. , Snega Priya R. , Saran G. , Sathya Priya M. 
Published: February 2021

Abstract
IoT is an evolving technology used in enormous applications in order to reduce the human intervention. As IoT is used in hybrid environment where it has to enable communication between multidisciplinary components it is facing lot more challenges. Security is the main issue had to be addressed. IoT devices are with limited power consumption; hence it’s not possible implement existing security algorithms as it is. Security attacks are increasing day by day; hence the dynamic solution has to be given rather than static solution. Machine learning is a promised technology that can be used in order to solve the security issues. This paper list out various work so far carried out in the area of machine learning for IoT security and solutions provided with future direction of research in this area.
A Multi-syndrome Pathology for Breast Cancer through Intelligent Learning
Authors: Vanitha C.N. , Malathy S. 
Published: February 2021

Abstract
The field of data analytics dealt with various methods to analyze the available data and help us to drawn into a point of conclusion about that information. Machine will learn the behavior based on the algorithms applied on those data and provide an appropriate conclusion. When these kinds of data analytic metrics applied to medical diagnosis various symptoms obtained from the patients and then the disease could be detected effectively. When certain optimization methods are applied on the data, the overall efficiency of the system will be improved considerably. To meet the challenges in diagnosing breast cancer based on clinical record sources, different symptoms in descriptions, clinical symptoms, a novel method, which consists of choosing the suitable features, multi-class functions, and multi-label parameters, has been proposed. The proposed work will be implemented as two steps such as discriminative symptoms selection and multi-syndrome learning. Public Breast Cancer Wisconsin (Diagnostic) Data Set has been taken for implementation. The breast cancer data set utilized for this work comprises 699 tumour samples. In that 458(65.5 %) samples belong to Benevolent (non-cancer) tumours and 241(34.5%) belongs to malevolent(cancer) tumours. The overall verisimilitude is 95.23% which will be improved to a greater extent when compared to the existing schemes.
A Comprehensive Review of Applications of Internet of Things for Covid-19 Pandemic
Authors: Malliga S , Kogilavani S V , Nandhini P S 
Published: February 2021

Abstract
Due to the raise of Covid-19 pandemic, there has been a surge in interest for the use of digital tools and technologies for pandemic containment While investigating, it is understood that the strategies based on potential digital technologies would definitely yield better benefits and these strategies have been recently used for controlling the pandemic In this article, we review how Internet of Things (IoT) and Sensors take health care to a new level and pioneers in addressing the Coivd-19 pandemic The recent cutting-edge IoT tools play a crucial role in restraining the spread of the virus and supporting the treatment of the infected persons This survey explores the recent IoT efforts and possible scenarios for addressing various Covid-19 issues like pre-screening, tracking of infected/quarantined people and many more We also examine the research opportunities that have been opened up due the application of IoT for the management of Covid-19 crisis Further, we have also identified a few challenges and issues to be addressed while using IoT during Covid-19 pandemic
Security Concerns during Photo Sharing in Social Network Platforms
Authors: Maragatham T , Yuvarani P , Sowndarya Shree J 
Published: February 2021

Abstract
The posting of pictures in online social media could be a common way of keeping buyers socially connected with others within the development of social media advances. The wealthy point of interest within the picture hence rearranges the suspicion of delicate information around individuals’ interior the photo by a malevolent client. In later a long time there has been a part of consideration to the way in which the security revelation of photographs was subsumed. When a client posts a photo, the picture must take into consideration the protection of all connected clients. This framework is anticipated to share such co-possessed pix. In addition to that, this approach proposes an eager way for the creator to track the edge, since of an equalization of privateers held with an anonymization and also with information traded with others. The anonymizing impacts of a picture are represented by an edge that’s characterized by the distributer. Simulation results uncover that the trust-based photograph sharing component is helpful to scale back the security misfortune, and furthermore the extended edge normalization strategy would pay a sensible taken a toll to the consumer.
RETRACTED: Intrusion Detection Using Machine Learning in Sensor Network
Authors: Ganesh Babu R , Vijay M , Parameswaran G , Anandhan C , Maurya Sudhanshu 
Published: February 2021

Abstract
An exhaustive assessment of the usage of machine and (Artificial Intelligence)AI answers for IDS structures in Wireless Sensor Networks (WSNs). To this end, introducing Restricted Boltzmann Machine-based Clustered-Introduction Detection System (RBMC-IDS) of conceivable AI-based IDS structure for WSN perception of explicit establishments. The RBMC-IDS display examination contrasts it and the recently presented adaptable IDS based AI. It Adaptively Supervised Hybrid IDS (ASCH-IDS). It mathematical results show that RBMC-IDS and ASCH-IDS achieve a comparative distinguishing proof and precision rates, anyway the disclosure period of RBMC-IDS is generally twice of ASCH-IDS.
BettaNet: A Deep Learning Architecture for Classification of Wild Siamese Betta Species
Authors: Pattana-anake Voravarun , Danphitsanuparn Pimsiri , John Joseph Ferdin Joe 
Published: February 2021

Abstract
Fish classification is a mix of animal sciences and artificial intelligence. With the advent of machine learning in artificial intelligence, classification has been done using computer vision algorithms and now deep learning is gaining prominence. Betta fish classification is not much explored. The wild species of Betta Splendens which are native to the Kingdom of Thailand are taken in the research reported in this paper. BettaNet architecture, a modified version of ResNet 152 is used to classify 6 species of wild species of betta. The experimental results show that the proposed BettaNet architecture holds better in performance in terms of accuracy and F1-scores. Two different datasets were used and the performance obtained by the proposed architecture reduced the cross-entropy loss over different experimental configurations.
Highly scalable and load balanced web server on AWS cloud
Authors: Mangayarkarasi M , Tamil Selvan S , Kuppuchamy R , Shanthi S , Prem S R 
Published: February 2021

Abstract
Most of the industries maintaining their web server on their on-premise, which leads them to have high maintenance, more workload, increases cost. To overcome this we can use cloud technologies for building a web server which gives better performance. Thus we use AWS cloud technologies. In this research paper, a web server is built using the cloud formation technique CFT. Using this technique we can able to build our infrastructure using YAML code. To achieve these major cloud resources are used such as Ec2 Instance, Application load balancer for balancing the load given by users, auto-scaling group. We will configure these cloud resources as YAML and implement them using the cloud formation technique. So that the industries can have their Infrastructure as Code.
A Review on Speckle Noise Reduction Techniques in Ultrasound Medical images based on Spatial Domain, Transform Domain and CNN Methods
Authors: Pradeep S , Nirmaladevi P 
Published: February 2021

Abstract
Ultrasonography is non-invasive and painless. In Ultrasonography the images are often affected with Speckle noise. It is a multiplicative noise. To help the doctors to identify the abnormalities properly there are several methods to diagnose as speckle is a major problem. This paper gives details about popular spatial domain, transform domain, CNN techniques for despeckling in ultrasound images. Transform domain methods like Wavelet methods, Curvelet methods, Bayes Shrink methods are prominent among many researches. Deep learning based methods are evolving like DnCNN, ECNDNet etc. for efficient despeckling. An overview of the methods is given here with certain measurement parameters like PSNR, MSE.
Diffusion convolution recurrent neural network – a comprehensive survey
Authors: Tamil Selvi K , Thamilselvan R , Mohana Saranya S 
Published: February 2021

Abstract
Graphs find its place in many applications like social network analysis, computer vision and bioinformatics. It has the ability to capture the structural relationship among the data, thus provides more insight. Graph Neural Network (GNN) has a deep learning way of analyzing the graph. The target nodes representation is obtained by iterative propagation of neighbour information until the stability is reached. Representational learning is widely used for capturing the insight of graph representation model. The complex structure of graph is hidden by representational learning results in shallow learning mechanism. Convolutional Neural Network (CNN) exploits the stationary properties and hierarchical pattern of the data which are in Euclidean space. Non-Euclidean characteristics of the graph can be captured precisely using graph convolutional neural network. In graph convolution, vertex domain is represented as aggregation of neighbour node’sinformation. In order to encompass the dynamics of graph, diffusion process is used, in which spatial dependency and temporal dependency are considered simultaneously. In Diffusion Convolution Recurrent Neural Network (DCRNN) uses diffusion convolution to capture spatial dependency and Gated Recurrent Unit (GRU) to capture temporal dependency. DCRNN is capable of handling long-term dependencies. In this survey, we conduct comprehensive survey on diffusion convolutional operations on graph, which is one of the most prominent deep learning models for forecasting in time series domain. First, we categorize the variants of graph convolutional models and its convolution operations on graph. Then based on application, graph convolutional models are categorized with their applications. Finally, open challenges in the area of graph convolutional network and future directions for research are discussed.
Optimization of aluminum alloy by CO2 laser cutting using genetic algorithm to achieve surface quality
Authors: SenthilKumar V , Nagadeepan A , Hubert Tony Raj L , Sabarish P , Stonier Albert Alexander 
Published: February 2021

Abstract
The cutting tool process became one of the uncommon thermal energy-based manufacturing methods used in aerospace and different electronics industries to create complex shapes on different metals and their alloys. This paper presents a genetic algorithm for optimizing wear rate and kerf width mostly during cutting tools of aluminum 6351 CO2. The experiments were based on the design of Box Behnken, which took into account three laser specifications for cutting process. Control of laser beams, cutting speeds and gas pressure. By reducing the surface roughness and kerf width, the optimum parameters for the laser cutting were determined. Our test results reveal that in solving optimization problems, the suggested genetic algorithm is efficient and efficient and can be incorporated into the intelligent production environment.