bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Coherent and Privacy-Protecting Biometric Authentication Strategy in Cloud Computing
Authors: Yadav Bonthala Prabhanjan , Prasad Ch. Shiva Sai , Padmaja Ch , Korra Seena Naik , Sudarshan E 
Published: December 2020

Abstract
The Biometric authentication has become progressively more desired in current years. With this expansion of cloud computing, database holders be influenced to expand this extensive volume of biometric information & detection operations to CLOUD for eradicate of this high-priced storage and result overheads, is still conveys possible dangers to users’ seclusion. In this document, we recommend an well-organized, well planned and confidentiality-protecting biometric classification strategy. Particularly, biometric information was encrypted & farmed out for Cloud database. For complete a biometric confirmation, server holder encrypts the inquiry information and proposes that to cloud. The Cloud implements recognition tasks on the encrypted server and sends this conclusion to the server holder. The systematic protection assessment specifies the recommended system is protected still if attackers can fake detection appeals and conspire through the cloud. Evaluated with previous protocols, investigational and new outcomes prove the recommended strategy accomplishes enhanced performance in both preparation and discovery measures.
Text categorization Performance examination Using Machine Learning Algorithms
Authors: Yadav Bonthala Prabhanjan , Ghate Sukhaveerji , Harshavardhan A , Jhansi G , Kumar Komuravelly Sudheer , Sudarshan E 
Published: December 2020

Abstract
Automated text categorization has been measured as a crucial technique for run and practice a huge quantity of papers in digital appearances that were extensive & constantly growing. In common, text categorization acts a significant responsibility in data mining and summarization, text recovery, and query responding. Interruption recognition scheme plays an vital responsibility in network protection. Intrusion recognition method was a analytical method utilized for forecasting network information collision is common or Intrusion. ML algorithms were utilized to construct exact methods to grouping, categorization & guessing. Labeled text papers were utilized for classify text with supervised categorizations. This article used these classifiers in many types for labeled papers & evaluates correctness to classifiers. An artificial neural network (ANN) method utilizing back propagation network (BPN) is worked by more than a few additional techniques to build a autonomous policy to labeled & supervised text categorization procedure. The obtainable standard mechanism was used for analyzing working of categorization utilizing labeled papers. Investigational examination on actual information discloses for mechanism runs good in stipulations of categorization exactness.
RETRACTED: A Comprehensive Study on the Various Applications of Deep Learning
Authors: Pranathi V. , Reddy G. Ranadheer , Sunil G. , Raghava Kumari D , Jamalpur Bhavana 
Published: December 2020

Abstract
Machine learning, using its analysis, is a region of computer technology that progressed stemming from examining style recognition as well as likewise computational learning concepts in an expert system. It is the learning as well as likewise building of protocols that might benefit from in addition to produce prophecies on data collections. These procedures operate by building and construction of a style coming from example inputs so regarding generating data-driven revelations or options rather than noting agency static device suggestions.
ECO Friendly Mask Guide for Corona Prevention
Authors: Tumuluru Praveen , Raju S. Hrushikesava , Baba CH. M. H. Sai , Dorababu S. , Venkateswarlu B. 
Published: December 2020

Abstract
At present, every live human being is worrying of COVID-19 and its varying forms to be attacked and its consequences. To invent the drug and vaccine, it is becoming a harder task that makes people hard to survive with this disease. Many people are getting this covid-19 because of contaminated environment as well as un-disciplinary actions. To avoid the spreading of COVID-19, the populace has to be aware with several sectors such as use of sanitizer, drinking of hot water, having of nutrition drink and hygiene food, and last but not the least consumption of immunity boosters. In this paper, we focus on developing an eco-friendly mask which not only prevents against COVID-19 but also purifies the air intake. The objective of this invention is to fight efficiently against COVID-19 pandemic in terms of preventing the spreading of Corona virus. The performance of this mask is validated against the conventional mask by considering and its maintenance will judge the success of this in the global mass society. Not only to face COVID, but also to face the pandemics to be raised in the future too. Hence, the proposed materialistic method using corona sensor will guide about corona surfaces and objects in the surrounding environment.
Multi Labeled Multi-Expressions to Explore Descriptive Documents
Authors: Thallapalli Ravikumar , Narasimha G. , Korra Seena Naik , Ravi Kiran K , Pallavi P. 
Published: December 2020

Abstract
Expressive Clustering contains ordinarily filtering through information occasions into get-togethers and making a practical plan for each get-together. The depiction should inspire a client to press ahead with no more prominent assessment of the specific occasions regarding the substance regarding each social occasion, enabling a client to channel quickly for suitable classes. Once in a while, the choice of delineations relies on anxious representation of heuristic data. We model and coordinate reasonable assembly that recognises highlights from bundle assignments and from a subset of highlights seeks bundle assignments. For updated extraction of Multi Labeled Multi-Word Phrases, we present a zone free clustering based way of thought (MLMWEs). The framework incorporates true information from Wikipedia articles from an all-around obliging corpus and connexions. We lace alliance checks to package MLMWEs through pieces of server homesteads and then the organising score for each MLMWEs subject to the closest model offered to a social affair after that process. Results of the assessment, A combination of association figures, achieved for two vernaculars, shows that an improvement in the organisation of independent and vital coefficient frequency controls and ultimately undeniable steps for MLMWEs is given.
Sentiment Analysis for Multi-Attribute Data in OSNs Using Hybrid Approach
Authors: Thallapalli Ravikumar , Narasimha G. , Pramod Kumar P. , Srinivas K , Pallavi P. 
Published: December 2020

Abstract
Increasing popularity of social networks like LinkedIn, MySpace and other networks in present days. Communication is also increased in between users present in social networks. Large amount of data being move on social media because of increase data outsourcing. Sentiment analysis is impressive and interest concept for online social networks, while different types of existing methods to find sentiment in online social networks to define communication between different users to categorize patterns with respect to similar attributes to analyze large data. We present and suggest the Hybrid Machine Learning method in this paper.(which is combination of Balanced Window and Classification based on Parts of Speech) to handle outsourced data of social networks from Face Book and other blogging services are trained and then classify the relation based on emotional aspect like positive or negative and other relations in social streams. The performance of our proposed approach is to extensively close to machine learning and identify important relevant features randomly and perform sentiment analysis in different data streams. Our experimental results show exhaustive level of classification results with comparison of existing approaches in real time environment.
Routing and data aggregation in wireless sensor networks by using clusters
Authors: Chythanya Kanegonda Ravi , Kumar Komuravelly Sudheer , Yadav Bonthala Prabhanjan , Madhuri P. M. , Mothe Rajesh 
Published: December 2020

Abstract
Due to the non-unique node distribution energy consumption existsdifferenceon the basis of clusters networks for wireless sensors. Based on this problem, we propose an effective communication and routing data aggregation tree based on the previous clustering architecture. Using fuzzy logic technology, cluster heads are chosen based on residual capacity, node density and heads for load clusters. Via modifying inter-cluster energy consumption, the algorithm for the energy usage of cluster heads between cluster routing balancing. Using the data correlation model, data compression is then applied to minimise energy consumption.
Survey on machine leaning based game predictions
Authors: Mohmmad Sallauddin , Nikhitha Madishetti V. , Nitin Yarra , Yadav Bonthala Prabhanjan , Sree Bommagani Sathya , Moses Beesupaka Marvel 
Published: December 2020

Abstract
In the world wide millions of people interested on games and competitive matches. The stakeholders stand for one team and produce the sponsorship to the players. Huge amount of money transferred from one hand to other hand. So that stakeholder wants to select a good players into his teams. Here Machine Learning based multi variant regression algorithms used to calculate the progress of each player based on previous datasets to predict the performance at on-going match. To extract the features from on-going match characterized with learned datasets by implementing the Support Vector Machine (SVM), Gaussian Fit-chime (GAU) and KNN algorithms which perform the optimal classification on trained datasets. Feature selection and game predictions are become critical analytical process. The performance of the model effected and produces the outcome based on the feature selection. In this process some irrelevant variables removed to reduce the burden of algorithms and input datasets dimensions. This process speed up the dataset learning using various algorithms to produce the game predictions. The machine learning models mostly preferred algorithms to implement in feature selection are Linear Regression, Decision Tree Regression, Random Forest Regression and Boosting Algorithm like Adaptive Boosting (AdaBoost) Algorithm. In this paper we discussed about how to predict the game score based on trained datasets using various algorithms on Machine Learning platform.
Study of threats associated with cloud infrastructure systems
Authors: Shiva Sai Prasad CH , Yadav Bonthala Prabhanjan , Mohmmad Sallauddin , Gopal M , Mahender K 
Published: December 2020

Abstract
Cloud infrastructure is the new euphemism in professional developers view these days round the clock. The rewards of cloud storage and its unique functionalities are absolutely massive and as such it is a concern of phenomenal significance. It offers various outstanding features such as Multi-tenancy, on-demand support, pay per use etc. This paper generates a report on the possible consequences of cloud computing. Processing infrastructure-as-a-Service illustrates the distribution of threats and how cloud doing so can affect their performance. The cloud infrastructure addresses the various situations where the attacks exist also the steps should be followed to mitigate the attacks. The research also tries at classifying steps have to take when using cloud services to reduce the impacts of undesirable consequences and to safeguard data integrity.
Fiscal Scam Illuminating Through Analyzing Human Behaviour
Authors: Sravanthi T. , Sruthi M. , Tharun Reddy S , Chandra Prakash T , Reddy Ch Vinay Kumar 
Published: December 2020

Abstract
Of these days, money fraud is turning into the employment of criminal practices wherever they will get involved, from senior managers till payroll workers, turning into a criminal sin. There are a vast number of methods that came into existence to analyze, find, and stop this behavior, which is the primary essential thing that is the fraud triangle linked with the standard evidence information model. By performing this study, a review of the connection works among the current literature was administered to build our framework. From this perspective, this paper explains about deception grasp; this framework allows the quality and exactness and disarray of people within a banking association who consign deception, reinforced by the fraud or deception triangle concept. This approach works amongst the permanent review, which can be liable for aggregating the agents to put into user’s assistance and encourage cybersecurity and the dropping of causes linked to financial fraud.
Data Integrity And Ensuring Computation Using MHT In Cloud Computing
Authors: Ghate Sukhaveerji , Yadav Bonthala Prabhanjan , Tharun Reddy S , Swathi N , Endla Purushotham 
Published: December 2020

Abstract
Basically, the architecture model of cloud computing provides the storage capacity as a service over the internet. The main intent of cloud computing is to provide services of security to the users and owners of data. Several security issues are appeared due to appropriate control of data. Hence in this paper the data integrity and ensuring computation using MHT in cloud computing is developed. In this first the data owner will select the initial parameters and choose the random function. The parameters are selected based on the generation of encrypted data blocks (EDB’s). After choosing function random key is computed. Now the Third Party Auditor (TPA) will initialize the data for verification. All this data is stored in the cloud server. This cloud server will follow the cloud service provider rules. Hence data which is obtained from server will computes and generate the signatures using MHT. After generation the path of the node will be identified. At last the obtained data is tested.
Analyze The Legislative Frameworkrelating to Surveillance and Right to Privacy: Issues and Challenges
Authors: Dule Chhaya S , Rajasekharaiah K. M , Prashanth B 
Published: December 2020

Abstract
India is world’s largest democracy of the world and accordingly protects free speech and expression through its laws and constitution, still freedom of speech and expression is not absolute and privacy in online sphere is being restricted for many reasons. There are several reasons for which speech and expression is being curtailed such as-defamation, maintenance of national security and communal harmony are major reasons for which they can be curtailed. Under the Indian Constitution, the scope of Article 21 is multi-dimensional. The laws of torts, criminal laws as well as property law also contain a right to privacy in this paper to examine the adequacy and balance between the privacy of the person and the protection and the safety of the country within the legislative structure relevant to surveillance. It is ironic that the majority of Indians were protected from cyber surveillance PRISM not because they were well shielded from any potential violation of their privacy, but actually because they were not yet able to be online. It also shows that even today, most Indians do not have computer access and do not have access to resources to ensure they are covered of any covert activity by surveillance agencies. But this is definitely not something that the government or the Indian people would stabilize.
RETRACTED: To Reduce Error Rate and Improve Performance of Classification Algorithm
Authors: Nagaparameshwara Chary S , Rama B. 
Published: December 2020

Abstract
In this paper, an improved method is introduced to reduce the error rate of the standard SD in the context of a two-class classification problem. The learning procedure of the improved method consists of two stages. Initially a shorter learning periodic carried out to identify an important space where all the misclassified samples are located. And the discriminative optimal criterion is computationally intractable as it involves probabilities that are not known a priori. And we have presented an algorithmic framework for feature selection based on nonparametric Bayes error minimization and our proposed framework offers sound interpretations over the existing approaches and also provides principled building blocks for establishing new algorithms. For example when weighted features are used as the search strategy as the framework reveals that the Relief algorithm greedily attempts to minimize Bayes error estimated by classification estimator. The new interpretation of Relief insightfully explains the secret behind the heuristically margin. the lower the error rate of the classifier. Consequently, the proposed improved method by its capability of achieving higher classification accuracy.
Tourism Enhancer App: User-Friendliness of a Map with Relevant Features
Authors: Dr. S. Hrushikesava Raju , Lakshmi Ramani Burra , Ashok Koujalagi , Waris Saiyed Faiayaz 
Published: December 2020

Abstract
There is many things to extract over a map that is dynamically available to the users. There are varieties of areas over a region in a map and are in traditional representation. To customize certain areas with own symbols from a pallet by providing prior guide, an environment that supports in user-friendly manner as well as rich built in libraries and simple graphical user interface is the python. With lot of built in libraries for this complex task, python takes less amount of code to bring the real time application compared with many other traditional programming environments. The guide to be intimated before using customized symbols for varieties of things in a particular location. This guide will easily help out how many are there according to category in that particular location. The end user might be aware of which country will be having highest number of that particular asset compared to other countries over a map. The information is worthy and is dynamic so, anybody will have accurate number of specific asset that required further analysis for their works. This information is similar to few apps like taking cursor over a region in a map, there playing radio or showing number of corona cases that are active. Information is wealth is the motto to make this paper as possible that demands the user to know anything over a region. So that, that region will be tagged with that specific asset which makes that location is popular and makes more tourism.
RETRACTED: Sturdy goals coverage for power harvesting Wi-Fi detector coterie
Authors: Chanti Yerrolla , Korra Seena Naik , Bhaskar Bandi , Harshavardhan A. , Srinivas V 
Published: December 2020

Abstract
Power harvesting Wi-Fi detectors Networks structure the dream of web of things frameworks. Vitality reaping hubs might be sent deliberately to screen at least one targets along with a valuable resource. Be that as it may, as these hubs depend on surrounding vitality assets along with sun oriented, they experience irregular power appearances. Subsequently, they may debilitate their collected force simultaneously as observing an objective. To this quit, network administrators require a tough arrangement that secure all goals are observed continually throughout whatever time length with a minded possibility. On this paper, we reckon three novel solid protection prerequisites; each essential safeguard with chance), where is the opportunity of fiascos. To start with, sensor hubs should now not go through more than their absolute collected vitality throughout T time allotments. Second, the power use of each detector hub need to no longer surpass the quality collected in each opening. Third the power consumption of sensor hubs should not surpass the power collected up to the current opening. We figure threat controlled stochastic applications that consolidate those necessities and cure them utilizing the example basic Approximation (SAA) technique. We affirm through tremendous reenactment examines that our applications are fit for figuring detector hubs actuation occasions that meet a given inclusion disappointment likelihood.
The comparative study on agglomerative hierarchical clustering using numerical data
Authors: Praveen P , Ranjith Kumar M , Shaik Mohammed Ali , Ravikumar R , Kiran R 
Published: December 2020

Abstract
In theconventional way of convert data into a singleton or merging has many drawbacks mainly computational complexity. In this context hierarchical clustering method for quantitative measures of similarity among objects that could keep not only the structure of categorical attributes but also relative distance of numeric values. For numeric data the number of clusters can be validated through integral data, the hierarchical and partitioning methods the relationships among categorical items. In This Paper we hereinvestigate linkage criterions in hierarchical clustering algorithm performance calculations using with Euclidian distance measure and some clustering techniques and their applications have been discussed. It also describes the necessities to be calculated for constructing a well-organized to handle the huge data sets. As the study initially investigates distinct issues for creating clusters with numeric attributes. The efficiency is obtained by clustering of datasets that comprises of numeric attributes related to distinct applications. Significant issues such merging object naturally uses Euclidean distance is resolved by using Agglomerative methods.
Innovative teaching practice on “software engineering laboratory course”
Authors: Harshavardhan A. , Ramesh D. , Kumaraswamy P. , Akarapu Mahesh , Jamalpur Bhavana , YerrollaChanti  
Published: December 2020

Abstract
Teaching Software engineering is very difficult because it includes theory and practical approach. Applying the theoretical knowledge is very complex. At the same time theory can’t be understood without applying. In this paper, we present an innovative teaching practice on the course “Software Engineering Practical” by which students will have a practical knowledge. We use different teaching steps and software tools to build an interactive lab atmosphere for the students to learn, recognize and understand the concepts of software engineering.
Secure Multiparty computation enabled E-Healthcare system with Homomorphic encryption
Authors: Vijaya Kumar A , Sujith Mogalapalli Sai , Sai Kosuri Tarun , Rajesh Galla , Yashwanth Devulapalli Jagannadha Sriram 
Published: December 2020

Abstract
With the spread of Covid–19 pandemic it is difficult for many patients to physically visit the Hospitals and get treatment. The Improved technology enable such patients to contact the concern doctors and get diagnosis information online. The security of the sensitive data of the Patients is vulnerable when the information is shared across the network. To address this, we are proposing a novel approach with the Privacy ensured self-care health management schema using Secure Multiparty computation (MPC). Through this approach the patient can share the sensitive data to the Hospital server through the online mode, the data will be shared in the encrypted format which will be matched with the existing data at the Hospital records and the best relevant match based on the smart Index of disease. The privacy preserving is key aspect in this model as the data is shared in the sensitive mode so the Homomorphic Encryption (HE) approach is used to perform computations on the Patient’s sensitive data in the encrypted mode and ensure the confidentiality from Intruders to access the information. This model also proposes a novel approach which can overcome many security threats. The patient’s data will be shared and used in a more secured manner so the patients specifically the elder who are not advised to visit the public places in this pandemic can also receive better treatment through online.