bluuebunny/crossref_metadata_2025 huggingface dataset:
Enhancement of Link Stability and Connectivity in Vehicular Ad hoc Networks
Authors: Et. al. Kishor N. Tayade,
Published: April 2021

Vehicular Ad hoc Networks is a promising sub-group of MANET. VANET is deployed on the highways, where the vehicles are mobile nodes. Safety and intelligent transportation are important VANET applications that require appropriate communication among vehicles, in particular routing technology. VANETs generally inherit their common features from MANETs where vehicles operate in a collaborative and dispersed way for promoting contact among vehicles and with network infrastructure like the Road Side Units (RSU) for enhanced traffic experience. In view of the fast growth of Intelligent Transportation Systems (ITS), VANETs has attracted considerable interest in this decade. VANET suffer from a major problem of link failure due to dynamic mobility of vehicles. In this paper we proposed a position based routing algorithm to identify stable path, this will improve the routing by decreasing overhead and interrupting the number of links. Link Expiration Time (LET) is used to provide the stable link, the link with the longest LET is considered as the most stable link. The multicast Ad-hoc On-demand Distance Vector (MAODV) is proposed to avoid the link breakages by using a link with longest LET.  Data loss is reduced by avoiding link breakages and enhance throughput by reducing the communication delay.
Features and Methods of Human Age Estimation: Opportunities and Challenges in Medical Image Processing
Authors: Et. al. Kirti A. Patil,
Published: April 2021

Age estimation of living species is an open and interesting problem due to its medico-legal importance and humans are no exception to this. Human body undergoes various physiological changes such as facial wrinkles, walking habits. Besides this, biological changes also help in human age estimation. Some of the changes are body skeleton and craniofacial growth. Various age estimation methods viz. manual, semi-automated and automated methods are available. Each of these methods has their merits and demerits. The popular manual and semi-automated age estimation methods are prone to human observation error and need sophisticated equipments. The advent of computational methods has opened new possibilities towards automation of the problem. Hence there is growing interest in fully automated methods. Through this paper, we have discussed different aspects of human age estimation and presented a brief review of various available methods.
Z-open sets in a Neutrosophic Topological Spaces
Authors: Et. al. N. Moogambigai
Published: April 2021

In this paper, introduce a neutrosophicopen sets in neutrosophic topological spaces. Also, discuss about near open sets, their properties and examplesZ-open set which is a union of neutrosophic P-open sets and neutrosophic δof a neutrosophicS Z-open set. Moreover, we investigate some of their basic properties and examples of neutrosophic Z-interior and Z-closure in a neutrosophic topological spaces.
Nnc Z∗-open sets in Nnc Topological Spaces
Authors: Et. al. K. Balasubramaniyan
Published: April 2021

The aim of this paper is to introduce and study the notion of NncZ∗o-sets in Nnc topological space. Some characterizations of these notions are presented
Trust-based Routing Protocols in Wireless Networks
Authors: Et. al. S. SriGowthem,
Published: April 2021

the Wireless sensor Networks is usually consisting of all-inclusive amount of bound sensor accessories which are announced in balance of the wireless media. As WSN’s become added and added capital to accustomed life, their aegis and assurance become a primary concern. However because of the attributes of WSNs, aegis architecture can be challenging. Trust-aware acquisition protocols play a capital role in aegis of Wireless Sensor Networks (WSNs). The key allotment of the acquisition agreement is avenue alternative based on account theory. Our after-effects announce that trust-based geographic acquisition approaches the ideal achievement akin accessible by flooding-based acquisition in bulletin supply arrangement and bulletin adjournment after incurring abundant bulletin overhead.
Some Studies on Fuzzy Generalized Open Sets
Authors: Et. al. Basayya B. Mathad,
Published: April 2021

Inw thisw paper,w wew introduce importantw fuzzyw generalizedw openw setsw namelyw fuzzyw Generalizedw Regularw openw (briefly,w fuzzyw GR-open)w sets.w Thisw neww classw showsw strongerw propertiesw inw fuzzyw topologicalw spacesw andw also,w wew investigatew fuzzyw GR-neighbourhoodsw andw fuzzyw GR-continuityw properties.
Viscous Dissipation and Suction characteristics of Heat and Mass Transfer past a Stretching Sheet.
Authors: Et. al. AlfunsaPrathiba,
Published: April 2021

in this paper, we analyzed the effect of a suction and Soret number on heat and mass transfer Magneto Hydrodynamics (MHD) flow past an exponentially stretching sheet with the heat source/sink. Appropriate similarity transformations were employed to convert the governing partial differential equations to a set of highly non-linear ordinary differential equations, which was then solved numerically by Runga kutta sixth order method together with shooting technique. The Numerical results are obtained for the skin friction coefficient, Nusselt and Sherwood numbers for selected values of the governing parameters, such as the suction, magnetic field parameter  , viscous dissipation parameter  , heat generation parameter  , Schmidt number  , and the chemical reaction rate parameter  . Besides, it is obtained that the concentration profile decreases with an increment of the Schmidt number. A comparison was made with a previous study available in the literature and we found that it is in a good agreement.
Analysis of M/G/1 Feedback Queue under Steady State When Catastrophes Occur
Authors: Et. al. S.Shanmugasundaram,
Published: April 2021

In this paper we analyse the M/G/1 feedback queue under steady states conditionswhen catastrophe occur. The stationary probability of  ‘n’ and zero customers sins the system are derived. The asymptotic behaviour of the model and the averages queues lengthare also obtained. The numerical example  are provided  to   test the feasibility of the model.
operator Proximity in i-Topological Space
Authors: Et. al. Yiezi Kadham Mahdi AL Talkany,
Published: April 2021

another form  of -operator defined in this paper by using employing two pillars they are i-topological spaces and the proximity spaces
Analytical solution of Velocities and Temperature fields using Homotopy Analysis Method
Authors: Et. al. Dr. K.V.Tamil Selvi ,
Published: April 2021

In this paper, analysis of nonlinear partial differential equations on velocities and temperature with convective boundary conditions are investigated. The governing partial differential equations are transformed into ordinary differential equations by applying similarity transformations. The system of nonlinear differential equations are solved using Homotopy Analysis Method (HAM). An analytical solution is obtained for the values of Magnetic parameter M2, Prandtl number Pr, Porosity parameter
R-Regular Integers Modulo
Authors: Rao M. Ganeshwar
Published: April 2021

Introducing the notion of ar-regular integer modulo we obtain some basic properties of such integers and arithmetic properties of certain functions related to them.
A Journal on Cervical Cancer Prediction Using Artificial Neural Networks
Authors: Et. al. K.Deepa ,
Published: April 2021

Artificial neural networks (ANN) assume a significant part in numerous clinical imaging applications. Cervical cancer ranks the 4th dangerous women cancers in less developed countries due to insufficient trained staffs and medical procedures. The location of cervical malignancy cells utilizes ANN for characterizing the typical and unusual cells in the cervix wall of the uterus. Cervical malignancy location is exceptionally difficult on the grounds that this disease happens with no manifestations.  The order between the typical,unusual and malignant cells produces exact outcomes than other manual screening techniques.The ANN utilizes a few models for a simple and precise identification of cervical cells. The main aim of artificial neural networks is to supply right information at a right time. Hence we implement artificial neural techniques with collected data Analysis,to improve the life of an individual and to decrease the death rate of the society respectively.
Performance Evaluation: A Glimpse of Its Prominence in This Modern Globalised Economy
Authors: Et. al. M. Subramanyiam Reddy,
Published: April 2021

Nowadays, performance evaluation has become an inevitable factor in the field of all sectors. It has become a formal procedure in measuring the progress of employee’s work scales. It is an important procedure in measuring the growth of work progress and it promotes the promotion of the employees. Performance evaluation helps in grading the employees annually and aids in salary raises. Further, it also enhances the quality of work progress, provides useful feedback regarding the work performed. This paper tries to investigate the importance of performance evaluation and its importance in the organisatinal sector. Further, this paper tries to underline the need for a performance evaluation system in the field of work in this present globalized technological world.
Optimal siting and sizing of multiple type DGs for the performance enhancement of Distribution System using Differential Evolution Algorithm
Authors: Et. al. N. Karuppiah,
Published: April 2021

The necessity of Distributed Generation (DG) in the modern power system has increased greatly. Optimal placement and sizing of DGs have a significant impact on the objectives of voltage stability enhancement, real and reactive power loss minimization and power system security and reliability. Different types of DGs such as Type I, Type II, Type III and Type IVare placed. The optimal placement of these DGs is found using Voltage Stability Index (VSI). The optimal sizing of these DGs is done using Differential Evolution (DE) algorithm. MATLAB simulation is carried out in standard IEEE 33-bus test system. The test is performed for various combinations of different types of DG. The results show that the voltage stability index along with Differential Evolution algorithm provides better voltage profile and power loss minimization as compared to the system without DG.
The Quest for Minority Rights in Federal Ethiopia: Legal Promise and Challenges
Authors: Et. al. Temesgen Thomas Halabo,
Published: April 2021

Ethiopia has adopted ethnic-based federal system as a response to National Questions in the country during the reign of EPRDF regime.  As this federal system is based on ethnicity, ethnic identity has become the key instrument regarding entitlement, representation and state organization. Now, the key to get access to the resources of the state is to acquire a separate ethnic identity and an ethnically defined administrative structure.

Based on the analytical literature review, the study has examined the challenges posed by ethnic-based federal system to protect the rights of minority groups and individuals residing within ethnically designated regional states.  The federal system has created its own types of political challenges for the protections of the rights of non-indigenous minority groups.  It is constraining rather than enlarging the political space for an overall citizenship. The idea of overarching citizenship that transcends ethnic identity is lacking in the federal system. The ethnic federal system also lacks mechanism for monitoring human rights at ethnically designated sub-state levels. The study, therefore, suggest reformulating the federal system, strictly respecting the principles of the federal constitution and revisiting regional state constitutions to avoid contradiction to the supreme federal constitution.
Do They Compute? Dawn of a New Paradigm based on the Information-theoretic View of Black holes, Universe and Various Conceptual Interconnections of Fundamental Physics
Authors: Et. al. Dr. Indrajit Patra,
Published: April 2021

The article endeavors to show how thinking about black holes as some form of hyper-efficient, serial computers could help us in thinking about the more fundamental aspects of space-time itself. Black holes as the most exotic and yet simplest forms of gravitational systems also embody quantum fluctuations that could be manipulated to archive hypercomputation, and even if this approach might not be realistic, yet it is important since it has deep connections with various aspects of quantum gravity, the highly desired unification of quantum mechanics and general relativity. The article describes how thinking about black holes as the most efficient kind of computers in the physical universe also paves the way for developing new ideas about such issues as black hole information paradox, the possibility of emulating the properties of curved space-time with the collective quantum behaviors of certain kind of condensate fluids, ideas of holographic spacetime, gravitational thermodynamics and entropic gravity, the role of quantum entanglements and non-locality in the construction of spacetime, spacetime geometry and the nature of gravitation and dark energy and dark matter, etc. to name a few.
Analysis of Archetypal Characters in Anita Nair’s Mistress and Lessons in Forgetting
Authors: Et. al. Hema. R,
Published: April 2021

The present paper analyses the archetypal elements present in the select women characters in the novels Mistress and Lessons in Forgetting. The archetypal presence is in the form of Indian mythological characters. This presence resides in the unconscious psyche of the characters Radha and Akhila. Radha identifies herself with mythological Radha and Ahalya. Akhila identifies herself with goddess Kanyakumari. The paper also analyses how these archetypal presence make them subjugated women and also how they help them to move beyond their stereotypical roles they play in the family and society. The characters Radha and Meera are ordinary women who emerge as potential, emancipated women at a later stage. They struggle in the process of transition from tradition to modernity. In their quest for identity, they emerge as strong and independent women. The paper is analyzed from Jungian perspective of archetypes.
Hotel Selection Criteria Among Customers with Reference to Bangalore City
Authors: Et. al. Bharath Booshan M S,
Published: April 2021

Hotel industry is considered to be one of the reputed industry  in India. The study is to analyse the attitude of the respondents towards discounting offers and attractive package given by hotels and to find out the impact of Price complexity, discounting offers and attractive package towards selection of hotels.  For this purpose a sample of 120 was collected from the respondents were percentage analysis, descriptive statistics, factor analysis, Kruskall wallis test, one way ANOVA  and multiple regression were used as tools to analyse the data. The conclusion of the study is that price complexity has higher impact on price complexity than other variables taken for the study. It is also concluded that the quality of service has to be enhanced in future period of time based on packages designed and discounting factors.
Power Efficient Two Transistor Exclusiveor Gate for Full Adder Usinggdi in 45NM
Authors: Et. al. J Nageswara Reddy ,
Published: April 2021

The principle part of ALU (Arithmetic rationale unit) is the Full Adder. This paper tells the best way to perform quick arithmetic activities created utilizing GDI. The fundamental point of this paper is to plan the full adder of two semiconductor utilizing Gate diffusion input (GDI) strategy. The plan of full adder is appropriate for the two semiconductor EX-OR gate. The primary intension of novel technique is fully founded on Full adder plan of 2TEX OR gate which is utilized to decrease power and improve the speed with an advanced territory of number of semiconductor check which is less similar with CMOS innovation. The best strategy for GDI is to plan advanced rationale circuits and which will in general improve the conditions.GDI system is functional to Full adder plan. The Cadence apparatus is to figure power, postponement and region for two semiconductor EX-OR gate .The total work is done in 45 nm innovation. The investigation of the outcomes show that the planned strategy is superior to traditional CMOS innovation.
Generate Various Parameters Of Trv Envelope Synthetic Test Circuit
Authors: Et. al. Jagadeesh Peddapudi,
Published: April 2021

The most basic transient a circuit breaker needs to suffer during its activity is the transient recovery voltage (TRV), started by the electric force system as a characteristic response on flow interference. To test high voltage CBs, direct testing utilizing the force system or short out alternators are not practical. The testing of high voltage Circuit Breakers (CBs) of bigger limit requires huge limit of testing station. An equal infusion of short out current and transient voltage to medium and high voltage circuit breaker (CB) by a synthetic model is examined. Transient recovery voltage is made by a capacitor bank and is applied to CB. An optical set off spark gap has been utilized to interrupt short circuit and to introduce of transient recovery voltage that is applied across the contacts of circuit breaker. Transient recovery voltage examination can never be done totally, as the advancement of circuit breaker development and organization configuration goes on. The most widely recognized way to deal with TRV examination is concerning the supposed planned TRV, in which a suspicion of dismissing association between circuit breaker itself and the innate system recovery voltage is being made. Notwithstanding, it actually is by all accounts qualified to examine what circuit breaker means for transient recovery voltage. An ideal grouping to open/close of reinforcement test article and helper circuit breakers inside suitable chance to infuse of recovery voltage. The impact of reactance of inductive flaw current limiter just as distance to blame in short line issue condition on pace of ascent of recovery voltage. A 4-boundaries TRV synthetic test circuit dependent on equal current infusion technique is planned and mimicked for testing 145kV rating circuit-breakers according to new TRV prerequisites given in IEC 62271-100.
An Efficient Class-Based Data Clustering Through K-Means And Knn Approach
Authors: Et. al. Kailash  Patidar,
Published: April 2021

In this paper an efficient class-based data clustering through k-means and KNN approach were applied. It has been applied for proper data grouping and efficient classification. In this approach three dataset have been considered for the experimentation. Data preprocessing has been performed for the removal of unmatched or empty entry. Then weight assignment and normalization has been performed. K-means and k-nearest neighbor (KNN) have been applied on the dataset for the data grouping and classification purpose. Different splitting variations have been considered with higher variance. Data selection is completely random. The results obtained shows the strength of our approach though classification and class-based clustering.
Analysis Of Alba Efficiency For Distributed Cloud Computing
Authors: Et. al. Madanmohan K,
Published: April 2021

Balancing the computational load of various simultaneous tasks on heterogeneous architectures is one of the basic prerequisites for efﬁcient use of such systems. Load-imbalance is naturally present if the calculation load is disseminated Non consistently across different tasks or if execution time for similar sort of tasks changes from one class of handling component to the next. Load-imbalance may anyway likewise emerge from causes that are outside the ability to control of the client, as case operating system jitter, over-membership of the accessible specialists, impedance and asset conflict by simultaneous tasks, and so on composing a fair equal application requires cautious investigation of the issue and a decent downplaying of different hardware architectures of the computing nodes.
An Enhanced Optimal Technique For Accurate Detection Of Color Face Images With Different Illuminations
Authors: Et. al. Ms. Meenakshi Shunmugam ,
Published: April 2021

Secured authentication system is one of the most challenging tasks focused now-a-days by many researchers and greatly achieved by means of face detection technique. Face image recognition is currently realized by Adaptive singular value decomposition in two-dimensional discrete Fourier domain (ASVDF). The recognition systems ability enhancement is attained for face images recognition by side light influence reduction on a color face image for inadequate light. The prevailing researches does not focuses the following points:  No correct output during face recognition process, Face spoofing is not concentrated thereby face recognition may effect in imprecise result, Optimal feature extraction. Optimized Face Recognition System with Illumination and Rotation Consideration (OFRS-IRC) is one of the promising solutions for mitigating all those issues. Various methods are presented for ensuring accurate face recognition. Additive White Gaussian Noise removal technique is utilized for eliminating noise when the image is captured through sensor devices. Illuminate invariant features and locality preserving projection approach is exploited for segmented image recognition. As a final step, Fuzzy neural network is deployed for precise prediction on the basis of locality preserving projection approach results. MATLAB simulation tool is exploited for evaluating this research, where improved performance are attained by proposed method than prevailing methods. The proposed method shows 7.42% better detection rate than the existing work.
Cat Swarm Optimization Algorithm For Antenna Array Synthesis
Authors: Et. al. Nirmala Yerpula,
Published: April 2021

Cat swarm optimization (CSO) is a developmental technique enlivened by the animals in Mother Nature for taking care of optimization issue. Short of what multi decade after CSO is proposed, it has been improved and applied in various fields by numerous scientists as of late. CSO is created by noticing the practices of cats, and made out of two sub-models, i.e., following mode and looking for mode, which model upon the practices of cats. The prerequisite of high directivity signal with extremely quick pillar guiding is preposterous by a solitary antenna. This imperative is aid by staged array antenna which is a mix of various little antennas that can create shaft with high directivity with quick electronic pillar guiding. The radiation example of an antenna array relies firmly upon the weighting technique and the math of the array. The issues related with pillar design causing high obstruction in communication which confine them use by and by. To beat these im-pediments, optimization innovation called Cat Swarm Optimization are applied in mix with the old style array blend strategies for staged array combination. An optimization issue is determined whose arrangement yields an ideal array for stifling impedance because of high side lobe level and grinding lobe. Results are introduced for ideal arrays of shifting array calculation, with various number of antenna components, and for distinct beamwidths and scan angles.
Empirical Study of Foreign Exchange Remittance of Non-Resident Indians
Authors: Et. al. Babasaheb Jadhav,
Published: April 2021

Remittances sent by migrants are an important component of the development finance for the countries. India has secured position as the world's top beneficiary of remittances with USD 80 million in 2018. The study was done in the Maharashtra State which leads the number in remittance (17%). The study highlighted the foreign exchange remittance behaviour of NRIs. The present study tried to understand the remittance behaviour of NRIs and remittance behaviour with respect to demographic profile .The remittance behaviour is studied with the help of demographic and non-demographic factors such as gender, age, occupation, education, purpose of remittance, frequency of remittance, risk in remittance etc.
Social Media Marketing and Bank Customers’ Behaviour: Conceptualizing a Relationship Model
Authors: Et. al. C.D Mudondo,
Published: April 2021

While research has underscored the benefits of social media marketing (SMM), organisations including commercial banks still fail to justify their continued investment in SMM, mainly because the full impact (of SMM) on customer behaviour remains unclear or largely researched. Thus, the aim of this paper was conduct an extensive literature review to develop a conceptual model to depict the proposed impact of social media marketing on commercial bank customers’ behaviour from a Social Exchange Theory (SET) perspective. Through an extensive review and synthesis of the literature on SMM, the researchers were able to theoretically postulate and propose the (possible) influence of the SET determinants inherent in SMM on commercial bank customers’ satisfaction, loyalty and their repurchase intentions. It is recommended that bank managers and marketers take cognizance of these (possible) proposed relationships, more specifically, the influence of the SET determinants inherent in SMM on bank customers’ behaviour. Furthermore, there is need to empirically evaluate the proposed conceptual model using data from a sample of bank customers and inferential statistics analytical techniques.
Distance Aware Gateway Placement Optimization for Machine-to-Machine (M2M) Communication in IoT Network
Authors: Et. al. Suvarna Patil,
Published: April 2021

In the research field, network performance for different smart applications plays an important role in the IoT network. Several factors, such as packet delay, network throughput, energy consumption, heterogeneity, proper gateway placement and load balancing, have a greater impact on network performance. In this article, two factors, such as optimal gateway placement and energy consumption, are investigated in order to improve the performance of the IoT network. Various methods are used to find the lo-cation of the Coordinating Devices (CDs) and to place constraint gateways in such a way that all CDs within the network should be covered by at least one gateway in order to allow the dissemination of data within the net-work. All of these CDs in the wireless network send their data to their near-by gateway based on Euclidean distance optimization. Euclidean distance performance is better than linear data transmission. During data transmission, nodes are unable to transmit data due to obstacles encountered in the path to the destination which result in a minimal energy efficiency improvement. Our proposed system solves the issue of gateway location optimization based on different distance-based approaches called Euclidean Distance (ED) and Manhattan Distance (MD) used in the wireless network to achieve the objective of reducing energy consumption.
Knowledge Management Practices in Steel Industries of India: A Comparative Analysis of Public and Private Steel Industries
Authors: Et. al. Srinibash Dash,
Published: April 2021

The purpose of this paper is to study the knowledge management practices of steel industries in India. The Indian economy is considered a mixed economy. Indian steel industry having the participation from both private and public sector enterprises is one of the fastest-growing industries in terms of steel production and is also increasingly looking towards export as driving the growth of the industry. Under this study both public and private steel industries are taken into consideration. The study was based on secondary data. This research brings a research report on the impact of Knowledge Management Practices (KMP) in the Indian steel industries. The analysis was made by taking the previous year's data regarding various matters relating to KMP and its pros and cons in the performance of the Indian steel industries. The comparison was done between these two i.e., both public and private steel companies of the country
A Neural Network in Convolution with Constant Error Carousel Based Long Short Term Memory for Better Face Recognition
Authors: Ramaraj P.
Published: April 2021

Unconstrained face identification, facial periocular recognition, facial land marking and pose prediction, facial expression recognition, 3D facial model design, and other facial-related problems require robust face detection in the wild. Despite the fact that the face recognition issue has been researched intensively for decades with different commercial implementations, it nevertheless faces problems in certain real-world scenarios due to multiple obstacles, such as severe facial occlusions, incredibly low resolutions, intense lighting, exceptionally pose inconsistencies, picture or video compression artefacts, and so on. To solve the problems described above, a face detection technique called Convolution Neural Network with Constant Error Carousel dependent Long Short Term Memory (CNN-CEC-LSTM) is proposed in this paper. This research implemented a novel network structure and designed a special feature extraction that employs a self-channel attention (SCA) block and a self-spatial attention (SSA) block that adaptively aggregates the feature maps in both channel and spatial domains to learn the inter-channel and inter-spatial connection matrices; additionally, matrix multiplications are conducted for a This approach first smoothed the initial image with a Gaussian filter before measuring the gradient image. The Canny-Kirsch Method edge detection algorithm was then used to identify human face edges. The proposed method is evaluated against two recent difficult face detection databases, including the IIT Kanpur Dataset. The experimental findings indicate that the proposed approach outperforms the most current cutting-edge face recognition approaches.
Effective Efficiency Evaluation for Solar Air Heater using Different Artificial Coarseness
Authors: Bharadwaj Gaurav
Published: April 2021

Effective efficiency evaluation is one of the important parameters in designing and selection of SAH. In this research article author have evaluated the effective efficiency of SAH using different coarseness configuration attached to the underside of collector of SAH used by various research. Correlation developed by various researchers for various coarseness has been used for the evaluation of effective efficiency. Effective efficiency evaluated for each coarseness used in SAH has been compared and suggested that which coarseness is to be used on the basis of comparison.
Impact Analysis of Hydration and Sleep Intervention Using Regression Techniques
Authors: Et. al. K. Reddy Madhavi ,
Published: April 2021

"Health is Wealth,"- The most well-known golden maxim, but most of the time, we ignore our health in favor of our professional pursuits. Good health covers not just our physical but also our psychological well-being. Individuals have forgotten that preserving our wellbeing contributes a large amount of effort to our advancement in this growing-race. Individuals agree that juggling the demands of life in clinical medicine poses a unique challenge, but good health can be sustained by drinking plenty of water and sleeping enough. We conducted an online questionnaire survey with a total of 30 questions, and the data gathered will be used to continue our hypotheses. Our main goal in this study will be to focus on the significance of drinking water and sleep respective to their age using machine learning regression algorithms. Therefore, a corrective statistical analysis can be predicted based on a dependent and independent variable.
Prediction of Climate Change using SVM and Naïve Bayes Machine Learning Algorithms
Authors: Et. al. C. Karthikeyan ,
Published: April 2021

Various reasons are there in failures of Intergovernmental Panel on Climate Change (IPCC) simulation model for prediction of climate change. For the better understanding of IPCC model’s failures by researchers, an improvement is qualitative and quantitative analysis is required and to be implemented. We come across a continuous crashes in simulation of Parallel Ocean Program (POP2) component of the Community Climate System Model (CCSM4), while measuring the impact of ocean model parameter uncertainties on weather simulations, during the period of uncertainty quantification (UQ) ensemble. This manuscript analyse the different machine learning algorithms, such as, Random forest, Linear Regression, k-means and naïve-bayes algorithms. From machine learning, a quality classifier called support vector machine (SVM) classification is used to predict and quantify the failures probability as a function of the values of POP2 parameters. Apart from quantification and prediction, this method performs a better understanding in simulation crashes in other complex geo-scientific models.
Fuzzy Detour Convexity and Fuzzy Detour Covering in Fuzzy Graphs
Authors: Et. al. R. Rajeshkumar,
Published: April 2021

A path P connecting a pair of vertices in a connected fuzzy graph is called a fuzzy detour, if its μ - length is maximum among all the feasible paths between them. In this paper we establish the notion of fuzzy detour convex sets, fuzzy detour covering, fuzzy detour basis, fuzzy detour number, fuzzy detour blocks and investigate some of their properties. It has been proved that, for a complete fuzzy graph G, the set of any pair of vertices in G is a fuzzy detour covering. A necessary and sufficient condition for a complete fuzzy graph to become a fuzzy detour block is also established. It has been proved that for a fuzzy tree there exists a nested chain of sets, where each set is a fuzzy detour convex. Application of fuzzy detour covering and fuzzy detour basis is also presented.
Connected and Total Vertex covering in Graphs
Authors: Et. al. Sathikala L,
Published: April 2021

A Subset S of vertices of a Graph G is called a vertex cover if S includes at least one end point of every edge of the Graph. A Vertex cover S of G is a connected vertex cover if the induced subgraph of S is connected. The minimum cardinality of such a set is called the connected vertex covering number and it is denoted by    . A Vertex cover S of G is a total vertex cover if the induced subgraph of S has no isolates. The minimum cardinality of such a set is called the total vertex covering number and it is denoted by  .In this paper a few properties of connected vertex cover and total vertex covers are studied and specific values of   and   of some well-known graphs are evaluated.
A Novel Groundwater Resource Forecasting Technique for Cultivation Utilizing Wireless Sensor Network (WSN) and Machine Learning (ML) Model
Authors: Et. al. K. Padmanaban ,
Published: April 2021

Groundwater is almost essential part of cultivation process, particularly in parched regions. The prophecy of groundwater intensity is crucial for understanding groundwater availability and provide systematic assistance for the cultivator that the stable convention of groundwater resource. A proposed efficient technique (ET) of forecasting the groundwater level (WFC) methodology was recognized in this study to precisely forecast groundwater intensity for cultivation in the parched regions of south India. Pumping facility, recharge capability of bore wells, exposure of cultivation area and weather conditions are used as key parameters, whereas groundwater level was considered as an output factor. The lack of systematic assistance about the groundwater availability also causes a decrease in the farmer’s emotional stability and thereby affects their plan of enlightening the right crops and craft financial hardship. The proposed technique can be a new method for forecasting groundwater resource. The analytical and prediction reports of the proposed method will assist the farmers about the accessibility of groundwater resource and lead them to plan the cultivation of right crops and prevent from economic defeat.
Facial-Based Cardiovascular Diseases Identification for Periodontal Disease Patients using Deep Learning Modified Neural Networks
Authors: Et. al. K .G. Rani Roopha Devi,
Published: April 2021

Challenging factor involved in the prediction of Cardio vascular Disease(CVD)plays a major role in a human health organization. Many prediction strategies still problematic for high-risk patients, most commonly the patient with continuous monitoring like elderly care and other correlated decease can lead to sudden Cardiovascular death (stroke, periodontal disease, etc) can involve in the high-risk category. The measurement and prediction always based on various testing factors involved in blood pressure, ECG, etc. Face emotional expression is a sort of discomfort behavior that gives the impression to be a universal factor of the pain experience. The remote heart rate measurement plays an important role in high-risk patients.In this paper, the facial-based Cardiovascular diseases are identified for periodontal disease patients using deep learning modified neural networks. The patient with periodontal disease can possible increased chance of Cardiovascular diseases. the classification can also be based on other testing consequences.
Structures, Operations and their Applications to Topology
Authors: Et. al. Geetha Jeyalakshmi  R,
Published: April 2021

A structure on a non empty set X is a collection of subsets of X. Any kind of topology on a non empty set X is a special structure on X. A filter and a filter base  on X  are examples of  structures. Also any ideal of subsets of X is a structure. In this paper several structures are classified and the binary relations  and operations on structures are discussed.  Furthermore structures on a topological space are also discussed.
An Optimal Feature Selection with Wavelet Kernel Extreme Learning Machine for Big Data Analysis of Product Reviews
Authors: Et. al. R. Sathya ,
Published: April 2021

In recent times, generation of big data takes place in an exponential way from diverse textual data sources like review sites, media, blogs, etc. Sentiment analysis (SA) finds it useful to classify the opinions of the big data to different kinds ofsentiments. Therefore, SA on big data helps a business to take beneficial commercial understandings from text based content. Though several SA approaches have been presented, yet, there is a need to improve the performance of SA to interpret the customer’s feedback and increase the product quality.This paper introduces a novel social spider optimization based feature selection based wavelet kernel extreme learning machine (SSO-WKELM) model. The proposed model initially undergoes pre-processing to remove the unwanted word removal. Then, Term Frequency-Inverse Document Frequency (TF-IDF) is utilized as a feature extraction technique to extract the set of feature vectors. Besides, a social spider optimization (SSO) algorithm is utilized for feature selection process and thereby achieves improved classification performance. Subsequently, WKELM is employed as a classifier to classify the incidence of positive or negative user reviews. For experimental validation, a Product review dataset derived from Amazon along with synthetic data is used. The experimental results stated the superior classification performance of the SSO-WKELM model.
Performance Analysis of Weld Image Classification Using Modified Resnet CNN Architecture
Authors: Et. al. Mohanasundari L,
Published: April 2021

The detection and classifications of weld images is important for improving the quality of the joined materials during production period. In order to automate the classification of weld images in industry, this paper proposes an effective automatic method for the detection and classifications of the weld images into four different cases using deep learning methods. In this work, Convolutional Neural Network (CNN) is adopted for the weld image classification by modifying the internal architecture of the CNN architecture. This proposed ResNet CNN architecture is designed with three Convolutional layers, two numbers of pooling layers with activation layer and two numbers of Fully Connected Neural Networks (FCNN).The FCNN in proposed CNN architecture is designed with 15 internal hidden layers and each hidden layer is designed with 20 neurons which obtains high classification efficiency. The morphological activity functional methods are used on the classified weld images to detect the crack regions.
Dynamics of the Stage Structured Population Model, Predator Accompanied by Michaelis Menten Holling Type Functional Responseand Delay and Prey Taking Refuge
Authors: Et. al. N. Mohana Sorubha Sundari,
Published: April 2021

The current work considers predator prey system, prey taking refuge, predator reckoned with time delay and Michaelis Menten Holling type II response function undergoing two stages: juvenile and mature. From the characteristic equation, we derive conditions for the local stability of the system at the equilibrium points. Also, at the coexistence equilibrium point, the system is analyzed for the occurrence of Hopf bifurcation. Lyapunov function provides sufficient conditions for the global stability of the system. Numerical simulations are given to support the theory.
Deduplication Supporting Strong Privacy Protection for Cloud Storage
Authors: Et. al. K. Makanyadevi,
Published: April 2021

Cloud computing is developing as the following disruptive utility worldview. It gives broad capacity capabilities and an environment for application engineers through virtual machines. Third-party inspectors (TPAs) are becoming more common in cloud computing implementations. Consequently, including reviewers comes with its issues such as belief and preparing overhead To achieve productive examining, we ought to (1) fulfill efficiently auditing without asking the information area or introducing preparing overhead to the cloud client; (2) avoid presenting unused security vulnerabilities amid the auditing handle There are various security models for safeguarding the CCs (Cloud Client) information within the cloud. The TPA methodically analyzes the prove of compliance with set up security criteria within the connection between the CC and the Cloud Benefit Supplier (CSP). A novel strategy to create the record for a copy check, and utilize a modern methodology to create the key for the record encryption. In expansion, the client as it were must perform lightweight computation to produce information authenticators, verify cloud information keenness, and recover the information from the cloud.
An Employment of Probabilistic Neural Network in Magnetic Resonance Imaging For Early Brain Cancer Detection
Authors: Sahym Seba Aziz
Published: April 2021

Given the circumstances of the countries in which wars, political instability, and other uncertainties are passing that make the atmosphere impure, which have caused many diseases, one of these diseases that has spread widely is cancer. Cancer is a very common disease, and many of them affect a person and lead him or her to death. Among these diseases, which have been common in recent years specifically the brain tumors that they need early diagnosis and do not cause the death of the person. Furthermore, many studies in the field of brain cancer detection have been done, but the best solution is still missing. Therefore, in this paper, a reliable method is proposed to detect brain tumors, extract its properties, and classify the tumor using Magnetic Resonance Imaging (MRI) through the artificial neural network.  In the proposed system, an essential part of image processing is the analysis and processing of digital images, especially to improve their quality, Bilateral Filter is used to improving image clarity and any image noise in this method preserves edges. After that, the distinctive properties of the image are extracted using the Histogram of Oriented Gradient (HOG) method. Thus, the extracted features are strong and can be classified as a Probabilistic Neural Network (PNN), this is what distinguishes our work from the previous works. The advantage obtained is granted to the PNN Classifier, which is used to train and test the accuracy of performance in perceiving the location of the tumour in MRI images of the brain accuracy as it resolves 99.5%.
Analysis Of Dynamics Of Business Environment And Their Impact On Human Resource Management
Authors: Kiradoo Dr Giriraj
Published: April 2021

Human resources have played a role in managing workplace complication as the business environment is continuously changing. The latest paper reviews the positive and negative impact on the organisation’s human resources resulting from the dynamics of technical, legal, political, and economic factors. The qualitative research technique applied in the study improves knowledge and systematically analyses resources. Research sheds light on how the technological environment, privatisation, globalisation, labour migration, changing social needs in the workplace and changing diversity affect the employees’ work. The research paper examines the business executive’s changing role in dealing with several human resource motivation activities and training to adapt changes to enhance competition effectively. Human resources are an indispensable organisational resource that needs to be adapted to changes to increase efficiency. Success and organisational efficiency depend on the knowledge, capability, and skills of human resources, which need to be reviewed and updated with a changing business environment. There is no loophole in achieving business success. The research paper noted a positive impact on organisational development owing to improved human resource talent competencies.
Effects of Self-Awareness and Sense of Belonging on Teachers' Professionalism
Authors: Et. al. Erna Kusumawati,
Published: April 2021

The purpose of this research was to determine the relationship between self-awareness and a sense of belonging to teachers' professionalism. The study strategy used is a quantitative correlation involving as many as 32 teachers in research subjects. By purposeful sampling, the subjects were chosen. Self-awareness scale, Sense of Belonging Instrument (SOBI), and scale of professionalism are the tools used. Analysis of data using partial correlation testing. The findings showed that there is a connection between self-awareness and significant professionalism with very strong criteria for correlation. However, with very low criteria for correlation, there is no significant relationship between a sense of belonging and professionalism. Then there is an important connection with low correlation criteria between self-awareness and a sense of belonging with professionalism. Each relationship has a positive direction for the relationship. The relationship between self-awareness, sense of belonging, and professionalism is clarified in this study.
Information and Communication Technology Integration on Human Rights Advocacy
Authors: Ashifa Dr.K.M.
Published: April 2021

The inalienable human rights codifications form the basis of human progress.  “The goal of this document is to resolve a current and significant problem regarding the convergence of human rights advocacy and the role of ICTs. It will promote efforts to advocate, educate and communicate with others, including media and political stakeholders within and outside the human rights world”[3]. The use of social media can consciously trigger the human rights movement and can also add to their outrage. Any public member or a human rights organisation sends the post, it is reasonably straightforward to explicitly concentrate public attention on social media. The present investigationtried to assess integration of online environment for human rights advocacy.