bluuebunny/crossref_metadata_2025_split huggingface dataset:
ZHLS Security Enhancement by integrating SHA256, AES, DH in MANETS
Authors: Barani Sundaram B , Mishra Manish Kumar , Thirumoorthy Dhanabal , Rastogi Umang , Pattanaik Balachandra 
Published: July 2021

Abstract
In this century fast growing and progressive change of technology, Mobile Ad hoc Network (MANET) which is a no centralized structure plays great role. The routing protocol in this network is objective to deliver efficient route since sender to receiver. One of the hybrid routing protocols example is Zone Based Hierarchical Link State Routing Protocol (ZHLS) that is can’t allowable huge amount of inside attacks which arise from malevolent nodes. The third party in the routing system may drop the data, as well as disturbs the progression of the routing. To resolve this difficult, ZHLS Security is enhanced by integrating SHA256, AES, DH in MANETS. Security to routing protocols in MANETS is incorporated with different traditional Security mechanisms. My idea behind this thesis is to use integrated security ZHLS protocol by integrating Advanced Encryption Standard (AES) as well as secure hash algorithms to provide the data security. Also, it is, Deffi-Hellman to preserve privacy among the data transmission nodes. In the proposed method, AES is applied to symbol, also authentication to provide the confidentiality of the message in the routing system. This work will be simulated on NS2 environment and it may highly improve the security of data transmission among wireless mobile nodes.
Study of Detection Analysis of Cardiac Amyloidosis Heart Disease Using Image Segmentation Technique
Authors: Jebakumari Gladys , Raaza Arun 
Published: July 2021

Abstract
Cardiac amyloidosis is a collection of mayhem, which increases the less important disposition of abnormal proteins in the heart. It may happen either in segregation or like a fraction of systemic disease and can be hereditary or attained. The major forms of amyloid proteins, namely Amyloid Light Chain also Amyloid Transthyretin (ATTR), can penetrate the heart. With the enhanced utilization of advanced image techniques and procedures, the identification and diagnosis of cardiac amyloidosis, especially ATTR, has become very easier. In general, congestive heart failure disease has been diagnosed through an electrocardiogram. In this survey, the ultrasound heart image is gathered as an input image to diagnose whether the heart’s functioning is normal or abnormal. Based on input ultrasound heart image or picture, the ultrasound high-frequency sound waves afford the heart’s image and valves, which allows us to observe the heart-pumping action. The image segmentation technique was well performed in segmenting the specified heart image into high-intensity range, and low-intensity level deliberated to enhance patients’ lives with cardiac amyloidosis. The disorders or variations or any abnormalities happening in the heart can be done via a segmentation approach through that intensity level.
Sliding Mode Control and Fuzzy With MPPT Control Based PV Integrated Grid System
Authors: MadhusudhanaRao G , Jayaprakash S , Murugesan R , Soundara Bala S 
Published: July 2021

Abstract
In this paper, the photovoltaic (PV) system based energy generation with grid integration of inverter and DC-DC boost converter. To enhance the system transient response and track the PV voltage in the load perturbations, the sliding mode controller (SMC) is implemented. The power conversion of DC-DC is accomplished using the converter controlled using the fuzzy logic controller with the MPPT control system. The proposed system increases the grid system stability, and it is achieving the quick settling time in power converter output, which means DC link voltage improvement. The results are achieved using the MATLAB/Simulink, and the obtained results are verified successfully.
A Shared Blockchain Intelligent Public Protection Service Framework
Authors: Reddy Gangireddy Prabhakar , Kalaiselvi Geetha M , SureshAnand M , Jaanaa Rubavathy S 
Published: July 2021

Abstract
With accelerated technical advancements in the IoT network, an intelligent scheme of public security is possible with the incorporation of heterogeneous data processing systems, with which public security services will collaboratively be provided. While this system design has always been pursued by IoT and Cyber internal environments, the provision of scalable and flexible IoT-based PLC frames in a legacy system is challenging. Traditional security techniques are sometimes founded on a tall structure which can be an in efficiency or a point let-down. Enthused through micro services also blockchain technologies, this article offers the Smart Public Security Architecture of Blockchain-Enabled Decentralized Micro services. A micro service-based authentication framework is implemented within a licence blockchain network for safe monitoring of data access in a PLC environment. Such functionality is divided into a single, intelligently organised package micro service which is dispersed at fog and edge node computing. A comprehensive experimental study found that the Blend MAS proposed would provide decentralised, scalable and secure intelligence gathering and access controls to the purchaser of IoT based PLC systems.
Community-Friendly and Cost-Effective Monitoring Device for Environmental Pollution Using IoT
Authors: Balarengadurai C , Akilandeswari A , Raja A , Kalimuthu K 
Published: July 2021

Abstract
Air contamination is today the world’s toughest problem for the environment and public health. Air contamination has a detrimental effect on the wellbeing of humans, the atmosphere and the biodiversity. Factory air pollution continues caused by leaked toxic gases, vehicle waste and increasing accumulation of unhealthy gases and particulate matter. Particular materials are among the principal parameters of elevated air emissions, including real-time air quality monitoring to be monitored and analysed to determine correctly in a prompt manner. A standalone air quality control system with many parameters in operation in real-time is introduced in this article: CO2, temperature, humidity, air quality PM 2.5 and carbon monoxide. In reality, in every sector, the Internet of Things is commonly used and is also a key factor in air quality management. The Internet of Things Cloud Computing is a new way of improving the data processing of multiple sensors obtained and transmitted by the low-cost Raspberry pi ARM minicomputer.
Connectivity and Mobility Awake Efficient Routing In MWSN
Authors: Lenin J. , Asha Shiny X. S. , Vanisree K. , Sivakumar P. 
Published: July 2021

Abstract
Mobile Wireless Sensor Networks (MWSNs) have established their applications in various streams, particularly in agriculture, forest fire detection, and military applications. However, insufficient bandwidth, communication faults, energetic topography, energy restraints, and stability of connection variations guide to node movement. However, the major problem is to link failures between sensor nodes. As s result, make the rerouting process create an additional delay. To solve the connectivity and Mobility Awake Efficient Routing in MWSNis introduced. We design this paper is mainly for monitoring crop agriculture also produce the supervise information to base stations. In this strategy, the dynamic connectivity is used to measure the node connectivity among nodes. Average encounter rate and the route encounter rate is applied to evaluate the node mobility. These three parameters are used to choose the best forwarder node in MWSN. Simulation results illustrate that improve the network performance equate to the baseline approach.
Cryptochain approach to Cloud Computing Security: Case study, Challenges, and Solutions
Authors: Mukherjee Subham , Sandane Raghav 
Published: July 2021

Abstract
Cryptochain has attracted the new generation of FinTech technologies because of its disruptive security that adapts to teaching time. In particular, it provides security with peer-to-peer authentication, encryption, and hash generation. According to the FinTech sector, the security market’s technology sector is predicted to grow to $ 20 billion at the end of 2021. With this, the cryptochain can operate across the whole Internet of Things (Cloud) ecosystem; its programs are predicted to expand. Cloud technology has been widely welcomed in all tech fields for its efficiency and reliability. This paper will discuss the theory of cryptochain technology and elated thermal research methods. We will learn how to sync cryptochain security on a cloud with its secure data solutions.
Segmentation of Services Provided by E-Commerce Platforms Using PAM Clustering
Authors: Gaikwad Divya , Lamkuche Hemraj 
Published: July 2021

Abstract
Today, data analytics have helped in solving many critical issues in various domains. From credit card fraud detection, detecting cancer to sentiment analysis, data analytics has come a long way. One of the important domains is e-commerce. With everything going digital, shopping has made its significant place in the digital world. A Partition around Medoids (PAM) clustering algorithm is discussed for grouping the services provided by e-commerce websites to their customers. The PAM clustering method helps to work upon real-time data with mixed data types. The clusters formed will provide better insights and patterns for the businesses to make better decisions in order to improve their customers’ engagement and multiply their profits using the historical data. With limited time and resources to invest, this method helps the company to proceed further by understanding the focus points of each service and their scope of development. Implementation of the proposed PAM clustering is done on the artificial dataset and is found to be effective.
Fusion of ACO and PSO Technique Based Optimized Routing for Intellectual Routing in Wireless Ad hoc Networks
Authors: Velmurugan A K , Madhan E S , Padmanaban K , Senthil Kumar A M 
Published: July 2021

Abstract
Wireless Ad hoc network (WANET) is an assortment of mobile nodes, which energetically custom a provisional network lacking the dependence of any infrastructure. In Dijkstra-Ant Colony Optimization Algorithm (ACO) forStraightas well asHarmlessEmigrationis applied to finding the shortest and safest path. However, this method cannot work perform when nodes are movable. In addition, ACO algorithm increases the power consumption and execution time. To solve the above problem in this work, Fusion of ACO and PSO technique based Optimized Routing (FAPO) for Intellectual Routing in WANET. This approachACOand Particle Swarm Optimization (PSO) technique is proposed to provide optimized routing and reduces link failures. The ACO and PSO techniquesinitiates with creating a greatquantity of mobile nodes in the search space and selects the route with high quality link. The function of the introducedtechnique is measured using the network simulator tool NS-2.
Analysis for Lossless Data Compression Algorithms for Low Bandwidth Networks
Authors: Semunigus Wogderes , Pattanaik Balachandra 
Published: July 2021

Abstract
Analysis for loss less data compression delivers the relevant data about variations of them as well as to describe the possible causes for each algorithm and best performing data types. It describes the basic lossless techniques of data compression Huffman encodes, Arithmetic Encoding, and Lempel Ziv Encodings then briefly with their effectiveness under varying data types of Latin text, audio and video. These properties give the solution of which lossless compression algorithm more suitable compared to other from the Saving Percentage, compression ratio, time of compression and time of decompression with Low Bandwidth Network. Moreover here Lossless Data Compression Algorithms (LDCA) being implemented and tested Huffman compression, Arithmetic compression, and Lempel Ziv algorithms, the implemented result shows that LZW algorithm saves more size than that of the others two with text file, Huffman compression algorithm saves more file sizes and the time takes to compressed decompress is higher than that of other two for audio file type and finally Huffman performs greater on very huge data compressions that is due to much compressing capability.
Understanding and Analysing Resource Utilization, Costing Strategies and Pricing Models in Cloud Computing
Authors: Ramesh Aishwarya , Pradhan Vishal , Lamkuche Hemraj 
Published: July 2021

Abstract
This paper is primarily focused on understanding the basics of cloud computing economics – specific pricing models and general cost structure and compares between basic cost structures. It also examines 15 pricing models dependent on various bases and attempts to consolidate the different pricing methods used to guarantee maximum profitability to both the service provider and consumer. To avail the services of cloud computing from the cloud service provider, the organization has to incur individual costs. There are three types of costs: fixed, variable, and semi-variable costs. Each type is computed and analyzed. There are more than 30 pricing models though the pay-as-you-go model, subscription model, and pay-for-resources models are in demand. To consider and discuss the basics of cloud computing, emphasizing its economics and pricing models considering various aspects and costing components, using and estimating plans from various cloud Registering suppliers. The paper also considers identifying gaps, if any, present in the current pricing models that are highly preferred with other pricing models that are designed but not implemented due to practical conditions and fear of higher percentage of risk and error and to compare the basic prices provided by the cloud service providers.
Power efficient in WSN supported clustering and tree technique
Authors: Nasurulla I , Kaniezhil R 
Published: July 2021

Abstract
WSN (Wireless Sensor Network), an outsized quantity of sensor nodes are establish and that they for the most part devour power in communicating information over significant distances. Sensor nodes are power unit managed and their power is compact. Compact power unit face the problem of limited power unit lifetime that has become the main issue in these networks and which represents to a test to their plan and the board. There are several forward (routing) protocols are implemented on WSN to transfer the info supported the top user need. The main goal (target) of the forward protocols is to compress the consumption of nodes power and develop the nodes life time. Between many forward protocols, In PEGASIS, there are so many used protocols; each protocol overcomes their drawbacks on further improvements. In this paper proposed a novel procedure by establishes a crossover calculation for clustering and cluster follower choice inside the WSN. After the decision of cluster leader and follower nodes, the proposed Tree method is set up for apportioning and preparing the information. The proposed plot productively reduces the unseeing transmission messages yet additionally diminishes the sign overhead in light of the fact that the aftereffects of cluster arrangement. Inevitably, the forward strategy is given upheld the layered design. The proposed Tree engineering productively limits the forward ways toward the base station. Complete investigation is performed on the proposed plot with cutting edge unified bunching and circulated clustering procedures. From the outcomes, it is indicated that the proposed plot performs better than LEACH.
IoT based Emergency Handling Communication System for Medical and Traffic Rescue Teams
Authors: Lenin J. , Divya Jyothi M. G. , Alzadjali Najiba Said Hamed , Azeem Sheik Abdul 
Published: July 2021

Abstract
Cloud Computing is a thriving technology, capable of revolutionizing the planet. On the Internet of Things (IoT), all objects across the universe have the potential to connect, which in turn provides the citizens with an understanding of everything. Many programs hire IoT to help people make their everyday life better, faster and healthier. In this article, we are suggesting an IoT-controlled emergency response system for Medical and Traffic emergency handling teams, which could be very useful when a vehicle is experiencing a catastrophic accident. A quick and accurate assessment of the extent of the incident is critical to improve the overall recovery method and enable emergency responders to properly determine the resources needed. The proposed device immediately starts to work when an emergency condition is observed. The program would initiate communication with the authority involved and sends critical and relevant details, such as the position of the incident, monitored health condition and photographs taken while the accident happened, using the camera. The device implementation uses Raspberry Pi 3 and required specific sensors.
A Surveillance System Focused On Approved Blockchains and Computation of Edges
Authors: Victor Benevent Raj A. , Srikanth B. , Thilagavathy A. , Mathivanan B. 
Published: July 2021

Abstract
Video surveillance systems have become a critical tool for urban management in recent decades. Without visiting the scene, managers may grasp the scene information. The monitoring system can improve management and supervision effects and reduce the likelihood of major accidents. With both the invention of the Internet of Things (IoT) era, however, sensor networks face difficulties, like massive access to equipment, massive data, inadequate bandwidth, attack vulnerability and real-time surveillance problems. We provide an overview of the implementations situation of the visual supervision system accordance with the project blockchain and border computers. The framework uses BCs, edge processors, developments from the IPFS and transformed neural networks. Edge computing is used for huge wireless communication collection and analysis. The IPFS storage service can be used and CNN infrastructure is used in legitimate surveillance to do a large video collection.
Prediction of the Speed and Wind Direction Using Machine Learning
Authors: Pattanaik Balachandra , Manikandan S. , Peniel Pauldoss S. , Gobinath S. 
Published: July 2021

Abstract
The wind is a free energy source; however, its high unpredictability is a significant integration problem of large wind power plant into an energy system. In a wind conversion system, the wind speeds are a vital power-generated tracking, regulation, schedules and dispatch and satisfy consumer requirements. This paper proposes using the machine learning (ML) based ant colony optimization (ACO) method for the wind speed prediction. A correlation among predicted and real data from climate models showed strong consensus. The significance of the current research depends on its ability to forecast wind speeds, a crucial precursor to performing successful incorporation of wind power.
Review for the Solar Radiation Forecasting Methods Based on Machine Learning Approaches
Authors: Hemavathi U , Medona Ann C V , Dhilip Kumar V , Raja Sekar R 
Published: July 2021

Abstract
Predictions of solar potential for these systems’ production are important, whether they ensure sound activity or the perfect control of an energy discharge heading to the solar system. It is important to base the prediction on solar irradiance before predicting solar systems performance. The measurement of solar radiation elements is a very significant criterion for applications of solar energy. Several globalized solar radiation prediction modes can be done in the two major categories: cloud imagery with physical models and machine learning techniques are correlated. In this paper, the methods used to predict solar radiation are explained with machine learning algorithms.
Machine Learning-Based Solution Predicting Hardware Faults
Authors: Ganesan R , Prabahar Godwin James T , Perumal P , Kumar Pardeep 
Published: July 2021

Abstract
Constant exploration of better performance and energy consumption has led to several hardware-based generators being used in interdependent SoC. Such generators abuse the intrinsic contrast of activities, and they also forgive inconsistencies in their outputs, such as image and optical machine learning applications. At about the same time owing to process growing and control constraints, irreversible faults are escalating, leading to incorrect outputs. Strategy to resolve this issue, which uses machine learning training tools to improve the impact of permanent fix in hardware accelerators that can withstand incorrect outputs. The suggested financial benefits do not need any accelerator details and are highly flexible with low capital areas. Furthermore, earlier work is very time intensive as it involves the introduction of fault pairs into the gate netlists to test their effect on the outputs. To solve these problems, this paper proposed to improve representation first by increasing the degree of complexity from the degree of both the gate to a stage of actions. The power to make segments and sub of the same contextual definition with specific features by establishing numerous propagation commands in the supply chain context involves. Test data demonstrate that our proposed approach is a simple and reliable way of generating different designs to secure the device.
Glaucoma Image Classification Using Entropy Feature and Maximum Likelihood Classifier
Authors: Rebinth Anisha , Mohan Kumar S , Kumanan T , Varaprasad G 
Published: July 2021

Abstract
In general, the nerve that links the eye to the brain is affected because of high eye pressure. The most common kind of glaucoma sometimes has no other symptoms than a gradual loss of vision. In this study, the Glaucoma Image Classification (GIC) is made by using different entropy features and Maximum Likelihood Classifier (MLC). Initially, the input fundus images are decomposed by using rankles transform, then the entropy features like sample entropy, Shannon entropy and approximate entropy are used to extract features. Finally, MLC is applied for classification. The GIC scheme’s function produces the classification accuracy of 96 % by using Shannon entropy feature and MLC.
A Distributed Fewer Environment for the Use of Blockchain IoT Device Sharing
Authors: Sundaramoorthy K , Thenmozhi E , Josphineleela R , Suma Christal Mary S , Shanmugapriya T. 
Published: July 2021

AbstractDue to the fact that the data markets become ubiquitous, it also becomes apparent that Internet of Things (IoT) applications produce data sources that are of benefit for future third party users. We are creating a marketplace for IoT data sources, allowing any pair of data providers and customers to participate in data transactions without any previous dependence on the shared trusts, to unlock those possible utility. We have a marketplace and architecture for the exchanging of streaming data, ranging from data publicity to legally binding exchange deals and payments. We prove that we can give participants an interchange of costs between the transactional data exchange and the possibility of loss of data when trading through unreliable third parties, through the use of blockchained technologies and smart contracts, in particular. On a test platform using Crypto currency Smart Contracts, we analyze these agreements experimentally.