bluuebunny/crossref_metadata_2025 huggingface dataset:
Recovery of niobium during comprehensive processing of pyrochlore-monazite-goethite ores
Authors: Permyakova N. A. , Tsygankova M. V. , Lysakova E. I.
Published: April 2021

This paper looks at the pyrochlore-monazite-goethite ores of the Chuktukonsk deposit (0.98wt.% Nb2O5) and their processing with the help of acidbased (HNO3, H2SO4) and sulphatization techniques. Nitric-acid pressure leaching was found to be an efficient processing technique for this type of ore: ore size –0.074 mm; CHNO3 = 25%; CH2O2 = 5%; τ = 2 h; solid-to-liquid = 1:9; heat treatment mode: 1 h at 160 oC followed by 1 h at 230 oC. As a result, rare earth metals and manganese are leached to the solution while all of the contained niobium remains in the cake. Two different techniques were tested to recover niobium from the cake. One is based on the use of alkali (NaOH sintering), the other is an extractive leaching technique that combines acid leaching with liquid-liquid extraction of tributyl phosphate in one stage. It was established that niobium mi nerals can be efficiently decomposed when using a mixture of hydro fluoric and sulphuric acids with the concentrations of 4.08 and 8.46 mol/L, correspon dingly, as a leaching agent. At the weight ratio of 1:2:1 of the solid to aqueous to organic phase and after the slurry has been stirred intensively for 5 minutes, niobium fluorides, which form as a result of interaction between hydrofluoric acid and the cake components, can be recovered with a 50% solution of tributyl phosphate in octane. After that they transfer to an organic phase while impurities get accumulated in the solid residue. As niobium-containing cake has a high concentration of silicon, it is recommended to first remove silicon from the cake using a strong alkaline solution.
AUDIOVISUAL CONTENT IN FOREIGN LANGUAGE TEACHING
Authors: Branko Medic, D.Sc. Xiaohui Sun, D.Ph.,
Published: April 2021

Following the recent dominance of videos as the most preferred content type among young learners, this research paper sets out the aim to investigate how audiovisual content can be used in foreign language teaching. The focus is on subtitling and captioning as two strategies often criticised by practitioners, yet widely adopted in the foreign language classroom. Empirical data is deployed to discuss both advantages and disadvantages of videos in the educational context. Findings are relevant for foreign language professionals who are willing to gain critical awareness on the latest Web 2.0 developments and to mindfully implement videos in class.
AGILE FRAMEWORK BASED IOT APPLICATION FOR FIRE DETECTION
Authors: Dr. Atul Patel Dhatri Raval, Dr. Jaimin Undavia,
Published: April 2021

The recent times the entire world is moving towards the automation and sensor based systems, applications and solutions. Tons of data are now generated without a single human intervention as the data collection is automated through such intelligent systems. Once you have huge amount of error free data with you, one can use it in various aspects for the betterment of any new system or system already on floor. The advent of IoT has changed the world of manufacturing industries too through installation of different sensors with high proximity. Such automated and intelligent systems are used to automate the routine process, signaling any accident, switch off/on any device which may lead to a hazard, automatic supervision of any process, etc. This article offers a framework to prevent fire accidents within the industry involving fire problems. The proposed system is going to be an IoT based solution with well equipped sensors and other triggering devices.
USING OSINT TO GATHER INFORMATION ABOUT A USER FROM MULTIPLE SOCIAL NETWORKS
Authors: Aditya Mahakalkar, Nihal Nakade, Renuka Lakhe Nilesh Sambhe, Piyush Varma, Arpan Adlakhiya,
Published: April 2021

With the widespread and easier access of the internet, many people have started to use various social networking sites each catering to their needs. It has been observed that most users prefer to use the same social media handle or username on multiple sites for easier management. This makes it possible to get a hold of the publicly available information about the user. But, with the increase in privacy protections and user restrictions, investigators often struggle to gather information about a user. We propose an automated software to perform this job which uses Open-Source Intelligence Gathering (OSINT) methods where all publicly available information of a user is gathered in an intelligently structured format all at one place. The software will search various social networking sites for the required user profile and gather all publicly available information. This information will then be available to investigators with the facility to export in various digital document formats.
REVIEW ON: WI-FI ENABLED APPLIANCES AND IT’S FUTURE CHALLENGES
Authors: Pande Sanjay P.
Published: April 2021

In current scenario, the term Wi-Fi is very much popular and familiar to everyone, it is seen that the world is moving towards wireless technology. Wireless networking is an upcoming concept of information technology. The networking that enables us to share information in the network to execute processes automatically, a human being can manage any application easily. The objective of this paper is to study Wi-Fi-enabled appliances used at home and offices, what is an impact on the people, how they react while working with wireless technology, and presents the future challenges. The technology for Wi-Fi enabled device is developed, but many issues need to be solved. When many users are trying to access a single Wi-Fi router at the same time. Then, due to shared bandwidth the signal strength decreases, causes delay in downloading, playing videos and finally data accessing and video streaming speed decreases. Also, power consumption increases due to the requirement of an uninterrupted power for 24x7 continuously. Thus, there is a certain scope for improvement in current technology. In this paper we proposed the concept of OTP based security key to restrict unauthorized access and the use of rechargeable battery-operated Wi-Fi unit for power saving purpose to resolve the future challenges.
MODELING AND SIMULATION OF STATCOM FOR POWER QUALITY IMPROVEMENT
Authors: Et. al. Ch. Umamaheswararao,
Published: April 2021

In power system, reactive power compensation is one of the important action to maintain better voltage profile, stability and decrease losses. STATCOM is feasible in terms of cost effective in wide range of problem solving capabilities among all Flexible AC Transmission system (FACTS) in both transmission and distribution levels. In this paper the synchronous rotating frame theory algorithm is used since it is easy to implement i.e. the rotating three phase quantities are converted into stationary components. So it requires less number of PI controllers and also calculations on the stationary quantities are easy than to do calculations on instantaneous quantities and the modeling of STATCOM is done.  This project focuses on improvement of power quality in a three phase three wire system with a non-linear load i.e., three phase bridge rectifier and a parallel inductive load. Some power quality aspects like reactive power compensation of linear load, better Total Harmonic Distortion (THD) performance and the power factor improvement are achieved. The result shows the THD of input current achieved as per the IEEE 519-1992 standard. It is observed that STATCOM gives effective compensation for reactive power variation and hence the power quality of distribution systems improved.
Synergetic Control Based Fast-Converging MPPT Technique for Thermoelectric Generator Energy System
Authors: Et. al. Polamraju. V. S. Sobhan,
Published: April 2021

Recently, waste heat energy recovery has attracted the attention of many researchers. The power conversion efficiency of Thermoelectric Generator (TEG) system is enhanced by designing suitable MPPT controller.  In this study a robust nonlinear control technique based on synergetic control theory is designed to extract maximum power from Thermoelectric Generator system (TEG). The designed synergetic control law ensures the fast convergence towards maximum power operating point without any oscillations under the presence of system uncertainties and variable temperature conditions. The TEG system comprises of a Thermoelectric Generator module, power converter, maximum power point tracking algorithm and load. The simulation results show viability of proposed strategy in comparison with Perturb and Observe (P&O) method under variable temperature.
High Gain DC/DC Converter with IC MPPT Algorithm For DC Micro-Grid Applications
Authors: Et. al. Subbarao Mopidevi,
Published: April 2021

High gain  DC-DC converter with IC MPPT algorithm, solar & wind as inputs in conjunction with this converter are presented in this paper. Recently, due to increase in the green energy demand the renewable energy resources are widely used.DC micro grids are now of significant importance due to the rise in DC loads and the demand for high power quality. These DC loads require various levels of voltage based on their power ratings. The proposed step-up DC-DC converter therefore has a high voltage gain with optimum duty ratio characteristics. In addition, the additional benefit of delivering electricity at two distinct voltage levels is that it is more suitable for DC micro grid applications and all the switches are controlled using single control signal which reduces complexity. The proposed converter is implemented and theoretically verified in SIMULINK MATLAB software for two different load power ratings of 100W and 200W.
Fault Tolerance Mechanism for Internet of Things (IoT) by Solving Nature Inspired Computing Algorithm (NIC)
Authors: Et. al. A. Prasanth Rao,
Published: April 2021

In clustering approach the sensor nodes are grouped to form a cluster. The nodes of a clustering network have low powered battery capability and limited processing capabilities. These nodes continuously exchange the data to cluster head which is in turn transforming the data to its base station. Few of these nodes in network may be faulty or may not support life time processing data due to its low power battery. All these sensor nodes measure the temperature, humidity, sound and pollution from environment and collected data is send to cloud for further processing. The fault tolerance mechanism of these nodes is solved by applying genetic algorithm by implementing chromosome technique to identify and avoid fault nodes in the network.  This proposed research work increases detection of fault nodes in a network, increase network efficiency, lifetime and reach energy optimization results in Internet of Things (IoT) concept. The performance evaluation shows that the data accuracy in Genetic Algorithm (GA) is higher when compared with Direct Diffusion (DD) Algorithm and Ad-hoc on demand Distance Vector (AODV) Algorithm.
REVIEW THE DEEP LEARNING TECHNIQUE FOR MISSING DATA CLASSIFICATION IN IOT APPLICATIONS FOR NETWORK PERFORMANCE IMPROVEMENT
Authors: Et. al. Gopal Patil,
Published: April 2021

In order to ensure product safety and increase production quality, The construction of mine Internet of Things networks continues to accelerate mining enterprises. Given the large increase in the number of networked devices connectivity capability in the mine, there is considerable strain on the mine network communication facilities. We suggest an Innovative Solution Using Deep Learning for Missing Data Classification in IoT Network Performance Enhancement System Market Classifier based on neural networks to improve the quality of service in the connectivity infrastructure of mine networks. The classifier uses a transformation wavelet to delete the data flow and to build compliance characteristics to identify the market categories of the system.Owing to the findings of the classification, the system changes the specifications of the network services given to the terminal equipment in a versatile manner. In this way, the system's network capacity can be fairly distributed. We assess the output of the classifier model using the test data collection. We review the deep learning technique in IoT applications for Network Improvement for missing data classification
A DATASET OF BEHAVIOUR OF PEOPLE DURING COVID-19 PANDEMIC IN A WELL DEVELOPING CITY, TAMIL NADU, INDIA
Authors: Et. al. P.Mukesh,
Published: April 2021

A dataset of human behaviour during the pandemic situation has been well analysed and reported in this paper. The nature of human behaviour has been dangerous due to high influencing of COVID-19 pandemic situation. This data set clearly describes the expectation of individuals, various communities, and necessity of the lockdown restriction based on the daily new Covid positive cases. It helps to analyse the behavioural response, social, individual expectations and health issues throughout the course of the pandemic period. The result of the present study clearly demonstrates that lockdown restriction highly helps to control the spread of the diseases, and the collective behaviour of humans in the initial period of pandemics depends on basic essential things for their day-to-day life. The dataset revealed that, behaviour of people and their needs has been changed and higher percentage of peoples are willing to go back their business and job to survive in the society against COVID-19.
A TREATMENT OF TOXIC SUBSTANCE IN PHARMACEUTICAL INDUSTRY WASTEWATER: A REVIEW
Authors: Et. al. P. Mukesha,
Published: April 2021

Pharmaceutical compounds are emerging environmental issue due to their continuous input and persistence to aquatic ecosystem even at low trace concentration. The aim of the present review is to find the effective way to reduce the pollutants in the pharmaceutical wastewater. There are several studies in the aim to develop new processes and new technologies to minimize the volume and toxicity of effluents generated by pharmaceutical industry wastewater. It demonstrates that Advanced oxidation process in a system can be a promising technology to treat pharmaceutical wastewater characterized by simultaneous presence of biodegradable and refractory inhibitory compounds.
ROBUST K-NEAREST NEIGHBOR CLASSIFIER AND NEAREST MEAN CLASSIFIER BASED INFORMATIVE KNOWLEDGE DISTILLATION FACE RECOGNITION
Authors: Et. al. M.Shanmuganathan,
Published: April 2021

Human Face identification procedures have made tremendous progress in the last decade. Nevertheless, identifying faces with incomplete impediment is as yet challenging for the present face identifiers, and  is very much required within certifiable application programs regarding reconnaissance and protection. Though great examination exertion has been dedicated to creating face de-impediment techniques, the greater part of them can just function admirably under obliged conditions. In this manuscript is proposed a Robust K-NNC (K-Nearest Neighbor Classifier) and NMC(Nearest Mean Classifier ) (RKNNC-NMC) prototype to efficiently reestablish incompletely occluded faces even in nature. This model comprises of two-stream, first introduced to perceive high-resolution faces and goal corrupted appearances with a student stream and a teacher stream, separately. A Teacher stream is signified by a Complex RKNNC-NMC for the sake of high-exactness recognition, and the student stream is signified by an a lot more straightforward RKNNC-NMC for low-unpredictability recognition. Broad examinations on synthetic and real datasets datasets of countenances with impediment plainly show the viability of   RKNNC-NMC in eliminating various kinds of impediment in one’s face at different locations. The suggested technique additionally gives better behaviour gain than other de-occlusion strategies in advancing recognition execution through partially-occluded faces.
FUZZY LOGIC BASED IMPROVED MEDIUM ACCESS CONTROLLER FOR CONGESTION CONTROL AND PREDICTION THE SYSTEMS IN WSNS
Authors: Et. al. M. Sri Lakshmi,
Published: April 2021

in resource-constrained networks, particularly those with limited bandwidth to manage high-volume data transmission, network congestion is a major issue, resulting in poor quality of service, including packet loss and delay throughput. Due to self-contained batteries that limit sensor node lifetime, this issue is important in wireless sensor networks (WSNs) with limitations and restrictions, such as limited processing power, memory, and transmission. By determining a path that avoids congested highways, the network can be extended. As a result, we present a WSN route determination architecture that is congestion-aware. The architecture is divided into three stages: In a top-down hierarchical structure, the first path is created. Energy-aware assisted routing for route derivation. Exponential smoothing is used to forecast congestion, but the final parameters for route determination are not taken into account. We use fuzzy logic systems to evaluate proper weights for a variety of factors, including shop count, remaining energy, buffer occupancy, and forwarding rate, as well as a bat algorithm to optimize the weight over the membership functions. Eventually proposed model shows the high throughput, low packet loss, save energy, and extending network lifetime.
Analysis of Motor Imagery EEG Classification Based on Feature Extraction and Machine Learning Algorithm
Authors: Et. al. Rameshwar D. Chintamani,
Published: April 2021

The brain-computer interface provides the excellent potential to address nervous system-related activity. The function of the nervous system work between internal brain control and external human body physical structure. Some parts of the human body cannot generate the signal for the processing of the human brain, cannot recognize and identify human body parts' activity—the motor imagery EEG classification approach helps resolve such types of critical illness cause of death. The dimension and structure of motor imagery-based EEG data are very high and unsupported behaviors. The machine learning and another classification algorithm cannot handle these variants of EEG data directly. For the process of better classification of motor imagery, EEG needs transformation and extraction. The transform-based feature extraction process such as DCT, DWT, SFTF and some other harmonic frequency-based applied. In this paper presents the details analysis of feature extraction and classification algorithms for motor imagery EEG classification. The machine learning provides three types of an algorithm for classification, supervised, unsupervised and semi-supervised. This paper mainly focuses on the supervised machine learning algorithm. For the analysis of machine learning algorithm use BC competition-IV dataset. MATLAB software is used as a tool for the code of algorithms and measures standard parameters such as accuracy, sensitivity and specificity.
Effectiveness of Adapted Science Instruction for Teaching Learning of Science Temperature Concept among Students with Visual Impairment
Authors: Et. al. M.Revathi,
Published: April 2021

The areas of science and mathematics have traditionally been inaccessible to students with Visual Impairment. Hence it needs adapted materials and instructional methods to understand and perform science experiments by visually impaired. This study aims to study the Effectiveness of Adapted Science Instruction on Leaning of Science Temperature Concept among students with Visual Impairment.  The Investigator adapted the Science Temperature concept Activities as per the needs of Students with Visual Impairment. Visually Impaired sample from Grade VI to VIII were trained and effectivess of the Adapted Instruction was found.
GENERATING ELECTRICITY BY FOOTPATH POWER GENERATOR FLOOR TILES
Authors: Et al. Dr. R. Mohanapriya
Published: April 2021

Walking is the most common movement in human life. When a person walks, he distributes energy to the road surface in the form of impact, vibrations, sound etc, due to the transfer his weight on the road exterior, through foot falls on the ground during a every steps. This energy Can be tapped and transformed in the practical form such as in electrical form. In order to develop a procedure to connect footstep energy, we are developing a footstep electricity generating device. This device, if embedded in the footpath can varying foot impact energy into electrical energy. The working principle, when a pedestrian step on the upper plate of the device, the plate will dip down to some extent due to the weight of the pedestrian. The descendant movement of the plate results in sturdiness of the piezoelectric materials fitted in the device to produce electrical energy the device was worked by persons walking over to it. However, if there is determined movement of pedestrians over the device, a large amount power will be a formed in this research a prototype of the power producing tiles is developed and studied under varying loading environments to inspect the feasibility of the technology.
Analysis of Delaminated Hybrid Carbon Fiber Composites in MODE-I
Authors: Et. al. Hassan A. Alessa,
Published: April 2021

Failure analysis of laminated composite structures has attracted a great deal of interest in recent years due to the increased application of composite materials in a wide range of high-performance structures. Intensive experimental and theoretical studies of failure analysis and prediction are being reviewed. Delamination, the separation of two adjacent plies in composite laminates, represents one of the most critical failure modes in composite laminates. In fact, it is an essential issue in the evaluation of composite laminates for durability and damage tolerance. Thus, broken fibers, delaminated regions, cracks in the matrix material, as well as holes, foreign inclusions and small voids constitute material and structural imperfections that can exist in composite structures. Imperfections have always existed and their effect on the structural response of a system has been very significant in many cases. These imperfections can be classified into two broad categories: initial geometrical imperfections and material or constructional imperfections
STUDENTS' E-SATISFACTION EXAMINED ONLINE COMMUNITY LEARNING, TECHNOLOGY FIT, AND COMPATIBILITY SEM – MODELLING DURING COVID19 PANDEMIC
Authors: Dr. Srinivas Subbarao Pasumarti Manoj Kumar, Dr. Pradeep Mamgain,
Published: April 2021

Pandemic outbreaks in student and teaching society have changed seriously. Now, with the influence of COVID19 infection fear, students have dramatically changed their orientational approach. Purposefully, University students aimed at connecting the virtual community for learning, interact, exchange information, and share knowledge. Numerous researched has examined the significant effects of the virtual community, although the present study aims to investigate the collective's e-satisfaction with the student e-learning environment at the university level as regards virtual community interaction, technology fitness, and compatibility. The study attempts to investigate the useful component for strengthening digital learning e-satisfaction by SEM modelling. This study focused on students from universities who take part in UG, PG and PhD programs from various parts of Indian higher education institution or universities. A total 384 number of responses were collected from the above academic intuitions. The study disclosed the importance of virtual community interaction, compatibility, and technology fit to measure e-satisfaction.
A Novel Fuzzy Inference System Based Robust Reversible Watermarking Technique provided with Six Layer Security
Authors: Dr. R. Balasubrimanian V. Belmer Gladson,
Published: April 2021

Digital Watermarking has evolved as one of the latest technologies for digital media copyright protection. Watermarking of images can be done in many ways and one of the proposed algorithms for image watermarking is by utilizing Fuzzy Logic. It is similar to the concept of a Fuzzy set, each element can be defined by an ordered pair, in which one is the value and other is the membership function value. Fuzzy logic systems can explain inaccurate information and explain their decisions. Fuzzy inference system is the simplest way of performing Fuzzy Logic. In the proposed method, three Fuzzy inference models are used to generate the weighing factor for embedding the watermark and input to the Fuzzy Inference System is taken from the Human Visual System model. The Performance measures used in the Process are Peak Signal to Noise Ratio (PSNR), Structural Similarity Index (SSIM), Normalized Cross Correlation (NCC) and Bit Error Ratio (BER). The Proposed algorithm is immune to various Image Processing attacks.
Improved energy efficient hierarchical cluster tree based routing to prolong network lifetime
Authors: Et. al. Venkatesh Prasad B S ,
Published: April 2021

Wireless sensor networks (WSN) play a key role in enabling wireless communication technology among several nodes to remotely communicate and exchange information. WSN consists of tiny sensor nodes equipped with battery, scattered in an area to gather information around an environment and send to data collection node known as sink or base station (BS). WSN have been widely used in various applications like agriculture, fire detection, health care and military and has become imperative necessity for future revolutionary area like UAV (unmanned aerial vehicles), IoT (Internet of things) and smart cities which employs large scale sensor nodes. However sensor nodes are limited to battery, memory, low computational power, resource and bandwidth. Continues sensing of events, makes node to drain its battery faster and goes dead fast. For resource constrained WSN, hierarchical cluster based approaches are considered as energy efficient and improves network performance for large scale WSN. Minimizing energy consumption and extending network lifetime are major challenging issues of WSN, clustering methods with optimized routing have offered solution to optimize energy utilization. To balance energy consumption and improve network lifetime many existing hierarchical clustering approaches have been proposed, however existing method does not consider rotation of cluster head (CH) and considers cluster head selection based on residual energy and distance parameter. In this paper we propose an improved energy efficient cluster tree (IEECT) based routing to improve energy efficiency of hierarchical cluster. IEECT considers modification of existing LEACH (Low energy adaptive clustering hierarchy) protocol to improved energy efficient LEACH by considering energy parameters like residual node energy and average network energy. IEECT accounts optimal number of cluster head (CH) and selection of CH is done using threshold value among sensor nodes. Proposed IEECT combines tree based routing and data aggregation scheme to maintain desirable quality of service. Simulation experiments are carried out by using network simulator. Performance of IEECT is evaluated in terms of PDR, delay, energy consumption, network lifetime and overhead.
Scalable Data Processing for Prediction, Batch Computation and Analysis and Response Times using Google BigQuery
Authors: Et. al. Gitanjali Sinha,
Published: April 2021

Computing a complex dataset analysis is tedious task because  distributed resource management is  difficult task. Google disperses the registering utilized by BigQuery across process assets powerfully which implies that we don't need to oversee figure asset, for example, bunches, register motor, stockpiling structure. Fighting commitments customarily require custom estimating (and esteeming) of unequivocal procedure gatherings, and this can change after some time which can be trying. Since Google logically assigns resources, costs are dynamic too. Google offers both a compensation all the more just as costs emerge elective where you pay for the data brought into BigQuery and subsequently per question costs. Since BigQuery is a totally managed organization, the backend game plan and tuning is managed by Google. This is much more direct than battling plans that anticipate that you should pick a number and sort of gatherings to make and to administer after some time. BigQuery consequently recreates information between zones to empower high accessibility. It additionally naturally load adjusts to give ideal execution and to limit the effect of any equipment disappointments. So getting benefits of BigQuery we did complex data analysis in huge amount of data set within a friction of second. Our result is showing the capability of our research work in the field of scalable data processing.
CONDITIONS FOR THE PROTECTION OF HUMAN RIGHTS WHILE COVID-19, LEGAL PRINCIPLES AND ADMINISTRATIVE BARRIERS IN UKRAINE
Authors: Et. al. Chystokletov Leontii Grugorovych,
Published: April 2021

The article describes both the administrative and legal principles of human rights protection in the context of the spread of coronavirus, which is used in Ukraine and all over the world on the basis of theoretical and practical methods. In this regard, the question of the efficiency of the measures to lessen the spread of the virus, made in connection with the new tasks of the state authorities and, first of all, health authorities, without violating the basic rights of the people becomes relevant. It is proved that the legal analysis of the ratification of international and domestic regulations indicates extraordinary opinions on the issue of ensuring human rights in an emergency relative to the struggle with the infection. Basing on international and national practice, attention is grabbed to the administrative and legal principles of ensuring medical confidentiality during the pandemic. It is shown that the disclosure of medical secrets is allowed in cases of suspicion of the patient intending to commit a crime or on the basis of a decision of a court. Current work provides guidelines directed at enhancing the measures for protecting peoples’ rights in the situation of suppressing the spread of COVID-19.
WMSN: ANALYSIS OF AGRICULTURAL SOIL ENVIRONMENT MONITORING USING WIRELESS MULTIMEDIA SENSOR NETWORK
Authors: Et. al. E.Manjula,
Published: April 2021

This paper proposes an environmental monitoring for agriculture soil using Wireless Multimedia Sensor Network. WMSN is used to monitor the agriculture soil environment.  In order to ensure optimal use of the sensor nodes in WMSN and accurate access to the collected data, the  routing protocols with both energy efficiency and quality of service ( QoS) properties are necessary for the transmission of photo, video and scalar data. This paper proposes a priority aware energy efficient QoS based data transmission for agriculture soil environment and also detects the pest. It utilizes the available bandwidth and data rate in the best way and in order to be more energy efficient during data transmission. For performance analysis, the proposed system is simulated using Java and the results of the experiments suggest that the proposed algorithm is more efficient compared to other methods in terms of delay and energy consumption. The sink node provides the solution based on these collected values.
AN ADAPTIVE RESOURCE SCHEDULING FRAMEWORK WITH SCHEDULE INTERVAL FILLING FOR CLOUD SERVICES
Authors: Et. al. B.SivaRama Krishna,
Published: April 2021

Application level resource scheduling in distributed cloud computing is a significant research objective that grabbed the attention of many researchers in recent literature. Minimal resource scheduling failures, robust task completion and fair resource usage are the critical factors of the resource scheduling strategies. Hence, this manuscript proposed a scalable resource-scheduling model for distributed cloud computing environments that aimed to achieve the scheduling metrics. The proposed model called " Modified Resource Scheduling with Schedule Interval Filling " schedules the resource to respective task such that the optimal utilization of resource idle time achieved. The proposed model performs the scheduling in hierarchical order and they are optimal idle resource allocation, if no individual resource is found to allocate then it allocates optimal multiple idle resources with considerable schedule intervals filling. The experimental results evincing that the proposed model is scalable and robust under the adapted metrics.
Computer-Aided Diagnostic System for Digital Mammography
Authors: Tanmay Ghosh, Khan Alamgir Yang Xingyao, Muhammad Fayaz,
Published: April 2021

In this work, Computer-Aided Detection (CADe) and Computer-Aided Diagnosis (CADx) systems are developed and tested using the public and freely available mammographic databases named MIAS and DDSM databases, respectively. CADe system is used to differentiate between normal and abnormal tissues, and it assists radiologists to avoid missing a breast abnormality. At the same time, CADx is developed to distinguish between normal, benign and malignant breast tissues, and it helps radiologists to decide whether a biopsy is needed when reading a diagnostic mammogram or not. Any CAD system is constituted of typical stages including preprocessing and segmentation of mammogram images, extraction of regions of interest (ROI), features removal, features selection and classification. In both proposed CAD systems, ROIs are selected using a window size of 32×32 pixels, then a total of 543 features from four different feature categories are extracted from each ROI and then normalized. After that, the selection of the most relevant features is performed using four different selection methods from MATLAB Pattern Recognition Toolbox v.5 (PRtool5) named Sequential Backward Selection (SBS), Sequential Forward Selection (SFS), Sequential Floating Forward Selection (SFFS) and Branch and Bound Selection (BBS) methods. We also utilized Principal Component Analysis (PCA) as the fifth method to reduce the dimensions of the features set. After that, we used different classifiers such as Support Vector Machines (SVM), K-voting Nearest Neighbor (K-NN), Quadratic Discriminant Analysis (QDA) and Artificial Neural Networks (ANN) for the classification. Both CAD systems have the same implementation stages but different output. CADe systems are designed to detect breast abnormalities while CADx system indicates the likelihood of malignancy of lesions. Finally, we independently compared the performance of all classifiers with each selection method in both modes. The evaluation of the proposed CAD systems is done using performance indices such as sensitivity, specificity, the area under the curve (AUC) of the Receiver Operating Characteristic (ROC) curves, the overall accuracy and Cohen-k factor. Both CAD systems provided encouraging results. These results were different corresponding to the selection method and classifier.
A COMPREHENSIVE REVIEW OF ENERGY-BASED ROUTING STRATEGIES FOR INTERNET OF THINGS
Authors: Et. al. Srinivasulu M,
Published: April 2021

IoT is the acronym for Internet of Things acronym. At present IoT is a buzzword amongst academia, research and industry communities. Everything surrounded by us have developed abilities to communicate via the medium of internet. The Routing information plays a vital role in establishing communication between nodes in the space of IoT. Maximum energy of such connected nodes is consumed in the process of routing the packets. In this context optimizing the network lifetime with minimal energy consumption becomes important for efficient implementation of IoT infrastructure. This literature review is has the objective to identify the limitations existing in improving the network usability and thus enhance the network lifetime. The focus of this review is to consider various parameters like Quality of Service (QoS), efficient node deployment techniques, Network lifetime for Wireless Sensor Networks (WSN). A comprehensive and systematic study of Routing challenges encountered in an IoT network is accomplished. Further the performance of various energy routing protocols are studied.
CONDITIONAL GANS AS A SOLUTION TO IMAGE-TO-IMAGE RENDERING PROBLEMS
Authors: Et. al. Aleem Ali,
Published: April 2021

In many existing solutions of image-to-image rendering problems, the only focus is to find the closest output of the Generative Adversarial Network (GAN). In this research article, authors propose a generative adversarial network, a solution to pixel-to-pixel rendering problems and reduced the loss function to the maximum under all interactions. For achieving the best result, we have considered the mean square loss function in the generator and binary cross for the discriminator. Our proposed model deals with not only images but also read sketches where the edges are not sharp too. We have used a facade dataset to test our proposed model.
TAMIL SIGN LANGUAGE RECOGNITION IN REAL TIME
Authors: Et. al. Manisha. A,
Published: April 2021

Communication is interchanging of ideas information or message from one person to the other person, sign language is made with the hand and other movement, including facial expressions and posture of the body used by the people of unable to speak and hearing, there are different type of sign language. Tamil sign language is the regional sign language, the aim of the work is provide the real time recognition of Tamil sign Language (TSL) in to Tamil letter, here we introduced the convolutional neural network (CNN) as a classifier used as training the Tamil sign language and predict the Tamil sign language, the process are divided in two section one is to train by using the keras model and the second section is the skin segmentation of the hand gestures in the region of the interest, there are two phase in training the model, having set of the hand gestures images in the training set and testing set by using the image train the model, the model occurred the 100% accuracy in the white background and good lighting condition, 97.5 % in the low lighting condition.
MAJOR TEN PARAMETERS OF PULSATING HEAT PIPE- A REVIEW
Authors: Et. al. Bukke Nagamuni Naik,
Published: April 2021

Thermal Management in the present issue in the modern era. The technology in heat transfer day by day is increased gradually especially in electronic device, space applications, hybrid vehicles, solar heater. These are the major areas where heat management are successfully research is going on Pulsating Heat Pipe is a two phase device where the heat transfer is takes place through sensible and latent heat. This paper gives an over review of the Pulsating heat pipe design, working principle, parameters which   effects the PHP, dryout condition and applications where PHP is used successfully research is going on. This paper addresses the fundamentals of PHP, an overview, and the applications of PHP.
IMPACT OF LOCUS OF CONTROL ON INVESTMENT BEHAVIOUR: A SEGMENTATION APPROACH
Authors: Et. al. Fiona Sheenu Francis,
Published: April 2021

Investment plays a vital role in a developing country such as India, as it provides the necessary funds for undertaking productive activities to be circulated in the economy. Savings are our country's largest source of investment. Investments are subject to the individual’s attitudes, beliefs and perceptions. As a result, the attitudes and expectations of investors have a major impact on their investment behaviour. Locus of Control is one of the most important factors that affect individual’s decision-making behaviour. Locus of Control is people's assumptions about what causes their lives to have good and bad outcomes (Rotter, 1966). It is said that there is internal and external LOC. Individuals with internal LOC assume they control their own destiny, whereas individuals with external LOC relate their experiences to destiny, luck or chance. Consequently, LOC has a great influence on an individual's investment decision-making behaviour. As a result, this study attempts to assess the LOC of an individual investors, segment them based on their level of internal and external LOC, and also to understand the impact of locus of control on the savings and investment behaviour of individual investors. The study revealed that most of the investors in Kerala were moderates and the locus of control of an individual investor affected their savings and investment behaviour
RETAILERS’ PERCEPTION TOWARDS PRODUCT DEMAND AND SALES DURING THE PANDEMIC PERIOD OF COVID19
Authors: Dr. Gayathri Band, Suraj Palod, Mitali Singh
Published: April 2021

ABSTRACT

FMCG sector is the 4th largest sector of the Indian economy. The purpose of this study is to analyse the change in sale of various commodities and change in purchase of consumers through retailer's perception during the pandemic COVID 19. In a shot to slow the unfold of virus, several countries have obligatory temporary closures to non-essential stores, bars and venues likewise as put a ban on massive public gatherings. As such, the marketplace for FMCG faces sizable changes and changes in demand for client grocery (CPG).

The study focuses primarily on the retailer perception of consumers and market behaviour towards choose fast paced trade goods. Total of 120 forms were collected using Random sampling. A logistic Regression was used to identify the factors which have an effect in the retailers’ business during this pandemic situation. The four most important factors that are important for the retail outlets to survive in the pandemic situations are Quality of supply, Years of existence, delivery services avialable and product demand. In food and beverages, staples has the highest demand, in home care the toilet care has the highest demand and in personal care hand sanitizer has the highest demand. We also find a change in trend of purchase by the consumers, where consumers prefer larger quantity purchase and monthly purchase instead of frequent or fortnightly purchases.
CAN INDIA EMERGE AS AN ALTERNATE HUB FOR CELL PHONE MANUFACTURING POST COVID 19?
Authors: Vandana Sonwaney Kaushal Buch
Published: April 2021

The COVID 19 pandemic outbreak has forced countries worldwide to undergo lockdown which in turn has brought economic stability to a standstill. The disruptions caused in the supply chain  due to restriction of flow of material across countries has been a wakeup call for many countries for employing a  de-risk manufacturing strategy and look for alternatives other than China by exploring various other promising countries. This research aims to understand the impact of COVID 19 on the global supply chain of cell phone manufacturing industry .The study gives an understanding on post COVID scenario of cell phone manufacturing industry in India considering the de-risk strategies employed by various countries. The research highlights the strengths and weaknesses of the current cell phone manufacturing industry, and also suggests key recommendations on the roadmap to emerge as the new manufacturing hub in near future.
Decisive factors for the adoption of E-Procurement in manufacturing firms in India
Authors: Kiran Karande Satyaodai Bhadaoria , Kiran Karande
Published: April 2021

E-Procurement is not only just a method for purchasing goods or ordering online but much more than that. Some firms adopt and excel in e-procurement, while others fail. This research was carried out among large scale manufacturers in India on the adoption of e-procurement. The research and study is based on three key objectives: to study the intensity, impact and challenges faced by the organizations in India in adopting E-procurement in their operations. A study of the major manufacturing firms working in India was included in the study. In attempting to decide the variables that impact the performance of e-procurement programmes, the analysis followed a descriptive approach. From a list of 233 major manufacturing firms, a sample size of 38 respondents was chosen. Data was obtained by floating a questionnaire from the respondents. The data obtained was thoroughly analyzed and displayed in the tables using SPSS. The study observed that most of the large scale manufacturers in India have welcomed e-procurement with various practices of e-procurement such as: online advertising of tenders, online short listing of vendors, online tenders submission among other items.
To reduce the Turn Around Time (TAT) of trucks and improve in-plant logistics
Authors: Dr. Prashant Barge Kautuk Timane, Puneet Gusain,
Published: April 2021

This paper talks about the reduction of in plant operations time and reduction of turn-around time of the trucks in any FMCG Company. The plant has almost 300 vehicles for loading and unloading. The current systems and process for receiving and dispatching of goods is poised with several challenges. This process with the inspection of material at the entry of a truck to the billing procedures in an effective manner is a challenge due to various constraints. The load, which needs to be dispatched in a day, requires a very less turnaround time of trucks but the actual time, when analysed, was significantly higher than what was required. Higher turnaround time was causing ineffective operations in terms of placing the vehicles in the plant by the transporters. Subsequently, there was a considerable deviation between the planned orders to be dispatched and actual dispatch of goods. The complete process was studied for identifying the loopholes and time motion study was conducted to analyse the current issues, which was leading to more VIVO time of vehicles. The whole process was analysed and thus major factors, which were causing the delay of the vehicles were identified. A survey was conducted to pen down the issues causing the problems in managing the in-plant logistics of the company. Results were analysed and was found that deployment of more manpower and optimizing the entire process would help only marginally towards achieving the goal. Hence, automating the redundant and time-consuming activities would help in achieving a considerable amount of reduction in the turn-around time of trucks. This will indirectly increase the dispatch quantities of the company. In addition, there is a requirement to redefine work, which would primarily mean altering the original process. Thus, various issues in the existing processes were identified and reduction in turnaround time was observed with the implementation of the new process and tools used to reduce the redundant processes
Implementation and Effectiveness of New Technologies in Housekeeping Department
Authors: Das Parikshit
Published: April 2021

When everything from front workplace to food and liquid has started the new technology within the same time work department additionally go with new technology they must not be in the age.  In nowadays in building and hospital or any tourist sector work can not be outlined as cleanup and maintaining totally different surfaces there's a such a lot issue on the far side that additionally. currently days every and each trade is functioning through a technology-driven transformation and there's no totally different in cordial reception industry additionally. In these topics we tend to are planning to highlights the present challenges that we face from the worker and therefore the best practices on new technologies which may be innovated for the building trade, and if it goes well then we are able to apply this new technologies effectively within the building in work department. it's the upper growth and the and therefore the and additionally the cut tools for the building and hospital trade also. These articles delineated  the teachers and up to date building work technologies effectiveness. This new technological innovation within the work service is made public on very cheap of the model guest cycle. fine quality technological service is that the pillar of the work department it will create the work easier. building work have to be compelled to be a IT savvy housekeeping, cross coaching for the worker, TV, radio lightweight curtain area service laundry assortment every and each issue that is an element of the work are going to be controlled from one device. If these all are often implementing in a very systematic manner within the cordial reception trade then it will cause be an enormous opportunities and future profit for the hospital industry.