bluuebunny/crossref_metadata_2025 huggingface dataset:
Effect of Electrolyte on the Performance of Supercapacitors
Authors: Verma Sonali , Padha Bhavya , Mahajan Prerna , Arya Sandeep
Published: April 2022

Various ecological issues as well as current energy crisis motivate the research for proficient energy resources. A majority of the present energy resources are intermittent and consequently there is an urgent need of proficient energy storage technologies. Supercapacitors gained tremendous scientific interest owing to their various significant advantages. Electrolyte constitutes one of the most important roles in electrochemical supercapacitors as their chemical and physical properties influence various essential factors like capacitance, power density, rate performance, as well as cyclic life. It provides ionic conductivity and influences the transfer and balance of charges between cathode and anode. Electrolytes are categorized into various types, such as aqueous, solid-state or quasi solid-state, and redox-active electrolytes. This review deals with the effect of electrolyte properties on performance of an electrochemical supercapacitor for building highly efficient supercapacitors for the competitive market of energy storage devices.
Perception Gap Analysis of Employability Amongst Academia, Information Technology Industry, and Fresh Engineering Graduates
Authors: Kamble Shekhar Arjun , Pandey Suruchi
Published: April 2022

Employability challenges of fresh graduate engineers are widely known and is well accepted globally. Hitherto studies have focused on improvisation required in the academic approach to bridge these challenges. One of the major shortcomings observed in this context is the lack of common understanding of concept, of employability by the important stakeholders of the ecosystem, i.e. academia, industry, and graduate engineers. Creating fresh employable graduate at entry level is a process, which is impacted by multiple factors and academia cannot be single handedly held responsible for the lacunas of the overall talent ecosystem. Authors in this research endeavor have tried to understand the perception of term “employability” for the IT Industry (employers), academia (faculties and training and placement officers), and fresh engineering graduates. The findings identified from the study are important in creating a common shared understanding amongst important stakeholders to channelize their precious resources and efforts in the right direction.
Soil Nutrient Index (NIV) and Chemical Composition of the Soils of Sirsa (Haryana)
Authors: Kumar Parul , Jain Sushma
Published: April 2022

The present investigation was carried out in a rural area, Nathusari Chopta of Sirsa district, in the pre-monsoon season of 2016. Soil samples were collected from some selected villages to assess the soil quality. Total fifteen soil samples were collected from the surface with a 15-20 cm depth and analyzed. There is not much variation in the soil fertility status in different villages under investigation. The soils are having normal pH (7.48 – 7.84), safe EC (0.42 – 0.63 dS/m), low to moderate OC (0.43 – 0.96 % by mass). Further, minerals like P, Ca, and K (NIV = 3) are highly present. The analysis showed that the soils were suitable for cultivation. Keywords – nutrient index, rural area, soil fertility, cultivation
Structural, Electrical and Optical Analysis of Barium Boro-Bismuthate Glass System: Opto-Electronic Devices
Authors: Attri Vikas , Khasa Satish
Published: April 2022

A Glass composition 25BaO-30B2O3-45Bi2O3 was synthesized using melt quench technique. The structural, optical, electrical and thermal behaviour of prepared glass sample was investigated using X-ray diffraction (XRD), Fourier Transform Infrared (FTIR) Spectroscopy, UV-Vis NIR, Impedance spectroscopy and Differential Thermal Analysis (DTA) respectively. XRD pattern of annealed glass sample, matched with diffraction profile of Bi45BO69 crystallite with size 49.83 nm. Optical parameters such as cut-off wavelength, bandgap, urbach energy and the refractive index were also calculated using UV-Vis absorption spectra for both samples. Dielectric parameters such as dielectric constant (ε’), dielectric loss (ε”), a.c. conductivity (σac) and loss tangent (tanδ) were also calculated for as prepared glass sample. The DTA curve shows crystallization ability and thermal stability of glassy sample. The synthesized composition was found to be promising material for applications like opto-electronic and energy storing devices, which enhance industry, innovation and infrastructure and ultimately enrich the sustainable cities and communities.
Advances in Graphene Based MEMS and Nems Devices: Materials, Fabrication, and Applications
Authors: L Saipriya , Deekshitha Akepati , Shreya Shreya , Verma Shubhika , C Swathi , C Manjunatha
Published: April 2022

Microelectromechanical systems (MEMS) are generally known as miniaturized mechanical and electro-mechanical systems, whereas NEMS stands for nanoelectromechanical systems. Graphene is an atomically thin material that features unique properties, such as high carrier mobility, high mechanical strength, and piezoresistive electromechanical transduction, which makes it an extremely promising material for future MEMS and NEMS devices. Design and fabrication of MEMS/NEMS devices using graphene process includes trench etching, wafer backside etching, graphene transfer, and mass release, which are described in a comprehensive manner. This review provides interesting perspectives for lock-in detection of weak fluorescent signals, NEMS position detection, electromechanical control of the on-chip transmitter, and single-photon-level fast electromechanical optical modulation. There are various applications of MEMS/NEMS devices, namely radio frequency devices, optic NEMS, pressure sensors, inertial sensors, which have been discussed in detail. The review mainly focusses on the devices made up of graphene (atom-layer distance of ~0.335 nm) as a main electronic/mechanical material due to its remarkable mechanical and electrical (Young’s modulus of up to ~1 TPa cm2Vs-1) and charge-carrier mobility of up to 200,000, which makes it an extremely promising membrane and transducer material for MEMS/NEMS system applications. Modern MEMS/NEMS experiments utilize mechanical resonators to push the bounds of force and mass sensing, demonstrate novel electromechanical circuit applications, measure the structural properties of materials are also covered in this review.
Energy-Efficient Routing in WSN: A Review
Authors: Jonnalagadda Suman , Shyamala K , Roja G
Published: April 2022

Research in WSN has been increasing tremendously throughout the years. Because of its reliability, flexibility, accuracy, and easy deployment, it has its wide range of applications in every field. They consist of small nodes called sensors and they are capable of communication, sensing, and computing. The important constraint associated with the sensors is the energy. To achieve this we need to employ better routing methods. Routing, energy conservation, limited resources, interoperability, security, and scalability are some of the challenging tasks that need to be addressed. Many routing protocols are developed for WSNs. The efficiency of the network, which depends upon the lifetime of the sensor nodes, can be improved through the clustering technology. It is a process to divide the SNs in the network field into various clusters. Each cluster in the network field has a Cluster Head (CH). This CH will be communicating to the Base Station (BS) or the Sink. A detailed review of the routing protocols that are efficient for energy in the WSN is presented in this paper.
IoT and Blockchain Rostrum 2021: Implementation, Challenges, and Future Phenomena
Authors: Julaya Aafrin Abdul Jabbar , Dave Dr.Akshara
Published: April 2022

IoT and blockchain are the area that focuses on the security of the data. So many researches are already addressed in this relevant domain. Still there are many opportunities in IoT that need to be addressed [1]. For example, as the number of devices are increasing, the memory space is decreasing, while using the network layer communications protocol for relaying datagram. Its routing function enables internet working, and essentially establishes the internet (IPv4 and IPv6), as well as security issues, such as vulnerable access control mechanisms [5]. This paper’s main objective is to focus on the advantages of blockchain and implement it on IoT. In this research paper, how the combination of blockchain and IoT can create the wonders in the field of data security of smart devices is also discussed. Moreover, based on the past data, some challenges of IoT are also addressed.
An Insight Into Indian Fruits and Vegetables SMEs Supply Chain: Indian Agrarian Sectors
Authors: Bisht Shweta , Gupta Abhinav
Published: April 2022

Globalization and monetary development have prompted the expanded significance of the horticultural areas in India. There is a fast underlying change in the horticultural business and food economy at a worldwide level. However, the supply chain complexities of Indian fruits and vegetables are numerous. These critical issues and challenges are necessary to be examined and to be worked upon for the betterment of the overall sector, domestically, as well as globally. The paper centers on supply chains engaged with the fruits and vegetable sector in India and the various issues and challenges that present and influence them. The plausible relief procedures identified with the distinguished issues and difficulties are additionally recommended. An illustrative exploration has been utilized for the study. The F and V inventory network is described and the significant issues are distinguished, which are largely affecting the gross efficiency of the supply chain. The present study involves a thorough review of the literature work available and gives an insight into how a fruits and vegetable inventory network involves different factors impacting its delivery performance and distribution. The issues and difficulties, influencing the development of Indian horticulture, derived out of such countless papers are identified with cold chain management, food quality and nutrition, government policies, etc. The study is focused only on perishable units such as fresh F and V.
Raman Spectroscopic Studies on Graphene Oxide – Europium Nano Composites
Authors: M a Anu , I Dhanya , S Heera , Prakash Rinta , Abraham Nikhila
Published: April 2022

Graphene based nano composites are receiving much importance in recent years due to the two-dimensional topology, high carrier mobility, luminescent nature, and ultra wide band gap transition. Here graphene oxide is prepared by modified Hammers method. Resultant residue of dark yellow color is filtered using Watt man No. 1 filter paper and is further cleaned by washing several times with 5% HCl solution and de-ionized water. Unexfoliated oxide is eliminated from the sample by ultra-sonication procedure for 30 minutes followed by micro-centrifugation under 4000 rpm for another 30 minutes. Vacuum annealing is done at sample at 60OC for 12 hours to get black graphene oxide powder and is labelled as Sample4. Europium (III) nitrate is added to 3g each of graphene oxide powder in 0.1g, 0.2g, and 0.3g concentration respectively labelled as Sample1, Sample2, and Sample3. Uniform mixing is done in composite samples. Morphological properties are analyzed through SEM. Surface topology of GO is like thin folded sheet, while that of Eu-GO is like that of spreading small nano materials on folded surface. Average particle size distribution is found to be 79.09 nm. Chemical composition and stotiometric ratio of different elements in the composites are quantitatively shown by EDX analysis. Raman spectra for Samples 1, 3, and 4 are shown. We can see that no shifting of peaks are observed in composites with respect to pure GO is an evidence of stable sp2 hybridisation and rigid oxygenated functional groups.
Augmentation of Soil-Moisture Retention with Natural Hydrogel Extracted from Fenugreek Seed Husk for Loamy Soil with Real-Time Monitoring Using FC-28 Sensors
Authors: Gopinath Rajesh , Manoharan Shimna , Likhith M , Bhuvan PG , Kailash Ranuva , Akash M , Anupama HS
Published: April 2022

In the industrial era, agriculture continues to be a strong force capable of altering any nation’s economy. In this context, the inflation will strive heavily upon its agricultural produce. In the looming threat of climate change induced draughts, the issue of water scarcity and consequent depreciation of soil-moisture levels continues to haunt farmers impacting both quantity and quality of produce. The present measures which are being employed to enhance retention levels of soil-moisture are chemical-based, and could lead to environmental consequences and health hazards. This research strives for a sustainable natural solution by studying the potential of Fenugreek seed husk extract as an alternative replacement. The study strives to take advantage of the presence of mucilage with hydrophilic galactomannan within fenugreek seeds. Soil-moisture sensors enabled with Wi-Fi modules and RTC timers were employed to facilitate smart monitoring and real-time determination in the lab-scale studies for loamy soil. The comparative performance analysis with synthetic hydrogel concludes the research highlighting benevolence of natural hydrogel in enhancing soil-moisture levels.
Synthesis, Characterization and Proton Conducting Behavior of a Novel Composite Films Based on Phosphosilicate / Polypyrrole (PS/PPy)
Authors: Chouri Praveen , Patil Nirdosh , Bidve Anilkumar
Published: April 2022

Various phosphosilicate doped polypyrrole proton conductive thin films composite membranes were successfully prepared. Phosphosilicate obtained by sol-gel process by mixing tetraethoxy silane with phosphoric acid at a molar ratio 1:5. The proton conductivity increased with increasing both the content of phosphosilicate gel and relative humidity. Temperature dependence of conductivity showed a Vogel-Tamman-Fulcher type behavior, indicating that proton was transferred through a liquid like phase formed in micropores of phosphosilicate gel. The high conductivity of 0.065 S/cm with a membrane containing 60wt'% of the gel was obtained at 60°C at 90wt'% relative humidity. Key words: Membrane, conductivity, polypyrrole, composites, solid state.
Seismic Horizon Estimation Based on Deep Learning Technique
Authors: Dodda Vineela Chandra , Kuruguntla Lakshmi , Elumalai Karthikeyan
Published: April 2022

The seismic horizons estimation from the seismic data is essential for structural and stratigraphic modeling of reservoirs. Until now, manual interpretation and semi-automated techniques were used to estimate the seismic horizon from the seismic data. However, the seismic horizon estimation takes more time and needs a human expert for analysis. To overcome those limitations, we propose a novel method to estimate the seismic horizon using a deep sparse convolutional autoencoder (DSCA). The convolutional layers in the DSCA network extract the complex features from the seismic data which improves the accuracy of seismic horizon estimation. The DSCA network is trained in a supervised way with the labeled seismic data. The performance of the proposed method is tested and compared with an existing method based on quantitative metrics such as Mean Squared Error (MSE), Coefficient of Determination (r2), and Pearson Correlation Coefficient (PCC). Experimental results prove that the proposed method has shown better results compared to the existing method.
Green Brands Representation Through Color Trademarks for Sustainable Business Practices and Environmental Concerns
Authors: Jananipriya R , Usha S
Published: April 2022

Color is an essential component in marketing since it serves as a tool for communicating with customers. Choosing colors according to culture is an additional benefit for marketers and marketers as it creates the appeal of products and services and helps brand-sensitive citizens distinguish between companies. Because of the focus and encouragement on eco-friendly products, green brand awareness is critical in the aspect of environmental sustainability and sustainable in the business. This product may become more popular in the market unless people are aware of it and take responsibility by eliminating non-eco-friendly products. Color trademarks assist to protect competitor organizations from employing color combinations that aid in brand recognition. This research uses SPSS to find the significant value of the hypothesis. Data are collected from 136 responses. Data are collected through Google form using a simple random sampling method. The hypotheses are tested using chi-square and ANOVA using the SPSS.
Impact of Pear-Shaped Nuclei on Fusion Barrier and Synthesis of New Elements
Authors: Jain Shivani , Kumar Raj , Sharma Manoj Kumar
Published: April 2022

In the present work, the importance of octupole deformation (up to β3) and related optimum orientations has been explored in terms of fusion barrier characteristics (barrier height VB and barrier position RB). For this analysis, the beams of spherical 48Ca and β2-deformed 48Ar and 62Fe are used with targets of β3-deformed 144Ba and 280Ra nuclei. The results obtained are discussed in reference to that of quadrupole deformation. Additionally, the effect of deformations up to β3 has also been explored by considering different nuclear potentials obtained with different choices of Skyrme forces (SIII, SLy4, SkT1, GSkI, GSkII, and SSk), which, in turn, modify the barrier significantly. Further, for the above considered nuclear systems, the capture cross-sections have been calculated using the Wong formula, by integrating over all the orientations, for the formation of heavy and superheavy elements over a wide range of center of mass energies.
Synthesis, Characterization and Antifungal Activity of Novel Thiazolo-Pyrimidine Fused Heterocycles
Authors: Hitesh Hitesh Amrutlal
Published: April 2022

In medicinal chemistry, nitrogen and sulphur containing heterocyclic compounds are well known for their therapeutic properties.(1) Among them thiazole and pyrimidine derivatives possess diverse pharmaceutical activities.(2,3) More particularly thiazolo-pyrimidine fused shows various therapeutically activities like, anticancer, antimicrobial, antibacterial effects, antiviral ,etc (4-7). Such type of fused heterocycles containing furan and naphthalene moieties has not been developed. Thus, the aim of the present work to study the novel fused thiazolo-pyrimidine derivatives, their characterization and antifungal activity. (scheme-1).
The Analysis of Ionospheric Turbulence By Using Wavelet Analysis for Earthquake Precursor
Authors: Thakur Monika
Published: April 2022

An earthquake is a trembling and shaking movement of the earth's crust produced by the rupture and sliding of a fault. A sudden elastic energy is released from rocks that are subjected to a large strain as a result of slippage and rupture along the fault line. Many publications related to earthquakes precursors have been released in the last twenty years in order to predict the earthquakes. Wavelet-based techniques have been implemented across several aspects in space research but many applications associated with them. The wavelet analysis is well adapted to analyzing turbulence as well as the signal attenuation properties in ionosphere data. The turbulent characteristic of the ionosphere has been investigated in the dynamic of ionosphere in-homogeneities and genesis. In this article, we will discuss what an earthquake is, its consequences, and the most common earthquake prone regions. Anyone may obtain a general overview of our endeavor by reading this document.
Seed Fortification Using Biofertilizers and Non-Biological Agents
Authors: Ethakoti Reddikavitha , Sundar Ranjitha Dhevi V. , Arunachalam Sathiavelu
Published: April 2022

Seed germination and vigor is a quality having detrimental effects on the crop and its economic traits, a significant factor to make agriculture sustainable and economical. Seed enhancements including fortification and coatings all aimed to protect and improve germination and initial growth from pathogens, adverse abiotic factors, and nutritional deficiencies. It is well established that rhizosphere microflora plays a prominent role in influencing plant growth. If this is altered or modified using beneficial microbial agents and/or adjuvants the seed germination and subsequent growth and yield are protected and enhanced. The seed enhancement with biofertilizers ranging from bacteria, fungi, algae, and/or their extracts/metabolites is advantageous from an environmental and financial point of view. Thus, in this current review, we present different methods and agents employed for seed enhancement and current trends.
Use of Machine Learning and Detect Fake Profiles in a Social Media Network
Authors: Bhari Purushottam L.
Published: April 2022

The social network has become an important part of our lives today which is prone to online impersonation as well as fake accounts. These online profiles are used by intruders to cause harm in online social networks (OSNs) in order to perform malicious activities in form of privacy intrusion like theft identity. So it becomes necessary in OSN, to identify the account whether it is real or fake. In this article we have proposed several algorithms for classification like deep neural network and SVM (Support Vector Machine) algorithm. It also studies comparisons of these methods for classification based on the spam account dataset that is used to select the best.
Application of MLOps in Prediction of Lifestyle Diseases
Authors: Reddy Manjunatha , Dattaprakash Brahmanand , Kammath Sandesh , Kn Subramanya , Manokaran Sumathra , Be Rangaswamy
Published: April 2022

Our health is the consequence of a combination of intricate and stabilized interactions between genetic elements, microbiome configuration, environmental impulses, and lifestyle habits. Knowledge of their contributions, as well as the complex network that connects them, is essential to analyze the underlying mechanisms and the onset of many diseases and can provide crucial information on their prevention, diagnosis, and remedy. We have seen advancements in data analytic methods to discover valuable patterns by analyzing great amounts of non-standard, heterogeneous, unstructured, and incomplete healthcare data. Not only does it help in decision making, but also forecasting. With the limited accuracy identified in machine learning models, we have implemented a process framework of Machine Learning Operations (MLOps) to develop a robust and collaborative platform for streamlining data and process integration and synergy through the automation of retaining, testing, and deployment.
Pancreatic Cancer Prediction Using Hierarchical Convolutional Neural Network and Visual Geometry Group16 CNN Approach on Accuracy and Specificity Performance Measures
Authors: V. Upendra , R Puviarasi
Published: April 2022

The main aim of the work is to measure the accuracy, sensitivity, and specificity in the detection of pancreatic cancer. Materials and methods: The dataset of 7390 images obtained from Kaggle for training (80%) and testing (20%) of the predictive model developed in Matlab and statistical analysis is done using SPSS software. The hierarchical convolutional neural network (HCNN) is used for developing the model and compared with the visual geometry group (VGG16) based model. Result: The predictive model developed using the HCNN algorithm shows an improvement in accuracy 94.8221.4705, specificity 88.49801.78406, and sensitivity 90.04601.79226 than VGG16 model with accuracy 94.3760, specificity 88.39200.1663, and sensitivity of 88.92600.5808 with the significance of 0.437, 0.497, and 0.165. Conclusion: The outcome of the study confirms that the HCNN based model appears to be of higher accuracy than the VGG16 based model.
Need for Technology Intervention in Functioning of SHGs Run By Tribal Women to Promote Tribal Culture
Authors: Jena Gopal , Swain Sukanta Chandra
Published: April 2022

Abstract: This study is to appraise the need of information technology for the functioning of Self Help Groups(SHGs) in promoting tribal culture related to their living, particularly for the sal leave gatherers and simple artisans that do bamboo works and crafts. Tribal women through the SHGs and information technology can be a potential source of promoting tribal cultural and facilitating economic development of the district as a whole. A small fraction of tribal women have access to smartphones. However, all of the tribal women who are the members of SHGs have their perception on smartphone. This study is based on the responses of 70 such tribal women on their of living., culture and perception on smartphones for social networking. On the basis of Analysis of Varience, it is found that technology intervention in the functioning of the SHGs has the potential to promote tribal culture.Key Words: SHGs, Tribal Women, Culture, Information Technology, Gatherers, Artisans, Nayagarh, Odisha.
Development of Y-Shaped Porous Anodic Alumina Humidity Sensor to Enhance Lower Detection Limit and Sensitivity
Authors: Alam Noor , Islam S.S.
Published: April 2022

The amount of water vapours in the air can affect the productivity and safety of many manufacturing processes, such as agriculture, pharmaceuticals, and semiconductor industries, as well as human comfort. The humidity sensors based on porous materials, such as Porous Anodic Alumina (PAA), have persuaded much attention because of their high porosity and tuneable structure. In this work, we have developed a PAA capacitive sensor using phosphoric acid electrolyte by the Differential Pulse Voltammetry method of anodization. The PAA-based humidity sensor shows ultra-high sensitivity, fast response, and a wide detection range of relative humidity (RH). Response and recovery time of the sensor are ~ 16 s and ~ 4 s, respectively at 64 RH%, and the sensor is capable of sensing 1-100 RH%. These results advocate that PAA is a propitious applicant for various humidity sensing applications, especially where low humidity detection is required i.e., paper, lithium-ion battery, tea industries, etc.
Developing Grow Light Spectrum Optimization Algorithm for Plant Models: Case Study of Spinacia oleracea
Authors: Reddy Manjunatha , Vasista Sumanth , Vasista Sharath , Abbasi Taher , Manokaran Sumathra
Published: April 2022

Evolution uniquely modulates plants’ efficacy in absorbing photons of different frequencies-high altitude crops have evolved to more effectively absorb bluer, higher-frequency radiation, while low lying marsh crops are more sensitized to redder, lower-frequency spectral regions. Research has shown that plants’ phenotype(s) and biochemistry are indeed affected by the distribution and intensity of light. For the model organism S. oleracea (spinach), we were able to empirically identify a unique spectral distribution to achieve a minimum viable level of output that reduces energy consumption by 21%, compared to standard LED spectrum distributions. Additionally, by applying the customized spectrum to P. vulgaris (common beans), we showed that the spectrum produced was indeed customized to S. oleracea and not generalizable to all plants. We empirically customized a spectral distribution to optimize Spinacia oleracea (S. oleracea) plants for desirable phenotypes, including height, stem width, and leaf growth. When applied with horticultural grow lights, our spectrum dramatically reduces energy costs but maintains crop yield and quality as compared to standard LED lights. We propose standardized morphological and biochemical optimization methods for whole plant and/or plant cultures using high-throughput manners.
Microwave-Assisted Fabrication of Cyclodextrin-Based Nanosponges for Solubility Enhancement
Authors: VIj Mohit , Wadhwa Pankaj
Published: April 2022

Cinnarizine is plagued by low aqueous solubility and thereby poor bioavailability. Thus, it could be a model drug whose bioavailability can be improved by enhancing its solubility. The present study focuses on the fabrication of cyclodextrin-based nanosponges using a microwave-assisted approach. Phase solubility studies were performed to shortlist the cyclodextrin. The manufacturing process was streamlined by applying the 3-factor, 3-level Box-Behnken experimental design to optimize the microwave power level, reaction time, and stirring speed. The batch with the least particle size and highest yield was finalized. The prepared nanosponges were characterized for particle size, polydispersity index, zeta potential, drug loading, entrapment efficiency, and FTIR spectroscopy. The in-vitro drug release showed a drastic improvement in the solubility and release of cinnarizine from the nanosponges as compared to that of the plain drug and drug-cyclodextrin physical mixture. The study proved the suitability of this system for the solubility enhancement of cinnarizine.
Entropy Analysis on Pulsating Flow of Oldroyd-B Nanofluid in a Vertical Channel with Thermophoresis and Brownian Motion
Authors: G Venkatesan , Anala Subramanyam Reddy , S Srinivas , K Jagadeshkumar
Published: April 2022

The magnetohydrodynamic pulsatile Oldroyd-B non-Newtonian nanofluid flow via vertical channel with Joule heating, thermal radiation, and viscous dissipation is investigated in the present study. The influence of thermophoresis and Brownian motion are taken into account. In this investigation, the Buongiorno model is used to analyze the entropy generation. The governing coupled partial differential equations are converted into Ordinary differential equations with the help of the perturbation method and numerically solved by using the Runge-Kutta 4th-order scheme along with the shooting method. The impacts of different emerging parameters for temperature, entropy generation, nanoparticles concentration, Bejan number, heat, and mass transfer rate are examined in detail.
MHD Pulsating Flow and Entropy Analysis of Micropolar Nanofluid in a Vertical Channel with Thermal Radiation
Authors: D Rajkumar , Anala Subramanyam Reddy , S Srinivas , K Jagadeshkumar
Published: April 2022

In this paper, we have explored the pulsating flow of a magnetohydrodynamic (MHD) micropolar nanofluid in a vertical channel by applying Buongiorno’s nanofluid model with entropy analysis. The effects of Brownian motion, thermophoresis, Joule heating (Ohmic heating), and thermal radiation are taken into account. The specified concept is significant in the fields of polymer engineering, cancer therapy, and nano-drug delivery. The perturbation approach is applied to convert the governing partial differential equations (PDEs) into ordinary differential equations (ODEs) and cracked numerically by utilizing the shooting process via Runge-Kutta fourth-order method. The flow influences of velocity, microrotation, temperature, nanoparticle concentration, entropy generation, and Bejan number are deliberated by plotting graphs and analyzed in detail for the various values of emerging physical parameters. The heat and mass transfer rates are given in a table.
Electroencephalography and Blood Cells Analysis for Cerebral Malaria Detection Using Deep Learning and Neural Networks
Authors: Rajagopal Sivakumar , Ghosh Auhona , Mohanty Nikita , Mishra Kartikey
Published: April 2022

Cerebral malaria is a clinical syndrome that is marked by the asexual parasitic form, 'plasmodium falciparum.' Early diagnosis can help in avoiding fatal and long-lasting neurological outcomes, such as severe psychosis, metabolic acidosis, and hypoglycemia. Therefore, the developed model aims to detect the same for narrowed down symptoms associated with the same. The design is divided into the following functions: the recognition of potential seizures in the patient and the identification of parasitic blood cells. In the first half, the deep-learning algorithm consists of a Neural Network Sequential model to grasp the exclusive electroencephalogram (EEG) features of epileptic seizures and also reveal the correlation between data samples that are successive to each other. The latter work focuses on inspecting the decompressed blood cells images that are fed into a deep convolutional neural network to distinguish parasitized cells from healthy cells. With this, the transfer of medical findings is also made effortless since compression of images is done without loss of valuable information.
Polyoxovanadate-Activated Carbon-Based Hybrid Materials for High-Performance Electrochemical Capacitors
Authors: Vannathan Anjana Anandan , Chandewar Pranay Rajendra , Shee Debaprasad , Mal Sib Sankar
Published: April 2022

Two different polyoxovanadates derivatives K5MnIVV11O33.10 H2O (MnV11) and K7MnIVV13O38.18 H2O (MnV13) have been studied to evaluate their electrochemical performance. These polyoxovanadates were deposited on activated carbon (AC) to prepare AC-MnV11 and AC-MnV13 composites. The electrochemical performance of the AC- MnV11 electrode exhibits the remarkable specific capacitance of 479.73 F g-1 at a current density of 0.4 A g-1, along with incredible power and energy density. Likewise, the AC-MnV13 exhibits a specific capacitance of 357.33 F g-1 at the same current density of 0.4 A g-1 with an energy density of 71.46 Wh kg-1. Interestingly, the AC- MnV11 could light up the red and yellow color LED bulbs for a duration of 80 and 60 seconds, respectively, indicating a considerable power density of the material. The AC-MnV13 electrode shows significantly less lighting up the 65 and 30 seconds period with red and yellow LED bulbs.
An Analysis of Emotion Recognition Based on GSR Signal
Authors: Dutta Stobak , Mishra Brojo Kishore , Mitra Anirban , Chakraborty Amartya
Published: April 2022

In our day-to-day life, the proper perception of emotion plays an important role in human decision making and behavior. Nowadays, a lot of research is focused on the evocation and precise detection of human emotion, which can be later utilized in a different set of arena. There is good amount of research on emotion detection through parameters extracted via Face Recognition and Speech Modulation, etc. However, there is a huge question on the accuracy or effectiveness of these results as these features can be controlled or manipulated by the subject/person. So, the next approach is the usage of Physiological Signals. These signals are generated by the Central Nervous System (CNS) and cannot be controlled or manipulated by the subject/person. In the proposed work, we have used Galvanic Skin Response (GSR) signals for emotion detection. It is an easily available off-the-shelf, non-invasive sensing device, and is easy to use. We have used different machine learning models to classify the various emotional states with better accuracy. The different classifiers that are used are the k-Nearest Neighbors (kNN), Support Vector Machine (SVM), and Logistic Regression (LR).
A Novel Prediction of Sales and Purchase Forecasting for Festival Season of Hypermarkets with Customer Dataset Using Apriori Algorithm Instead of FP-Growth Algorithm to Improve the Accuracy
Authors: Karthik Somu , C.M. Velu
Published: April 2022

Aim: To predict the novel and to forecast sales for festival season hypermarkets. Materials and Methods: A total of 484 samples were collected from market datasets available in kaggle. For this two algorithms were used, one is the FP-Growth algorithm and another is Apriori algorithm. Both the algorithms were executed and compared for accuracy. Result: Apriori achieved accuracy, precision, sensitivity and specificity of 73 %,75%, 78%,and 80%, respectively, compared to 71%, 73%, 76%, 75%, and 78% by FP-Growth algorithm, 87.4%, 88.2%, 89.2%, and 93%, respectively, compared to 80.1%, 83.39%, 84%, and 86.20% by Apriori algorithm. The results were obtained with a level of significance (p<=0.310). Conclusion: The applied Apriori algorithm confirms to have higher accuracy than the FP-Growth algorithm. It was additionally found that FP-Growth calculation takes more modest time than Apriori calculation to yield novel results.
Medical Image Prediction for Diagnosis of Breast Cancer Disease Comparing the Machine Learning Algorithms: SVM, KNN, Logistic Regression, Random Forest, and Decision Tree to Measure Accuracy
Authors: Dinesh Paidipati , P. Kalyanasundaram
Published: April 2022

Machine learning using data mining techniques are used rapidly in medical research to predict the disease diagnosis. The aim of this study is to evaluate the performance of SVM, KNN, Logistic Regression, Random Forest, and Decision Tree. Materials and Methods: A Total of 569 samples are collected from the UCI Machine Learning Laboratory. The samples are divided into benign and malignant cells using groups like SVM, KNN, Decision Tree, Random Forest, and Logistic Regression to compare the performance of benign and malignant cells. The required samples for this analysis are done by G power calculation. Minimum power of analysis is fixed as 0.8 and maximum accepted error is fixed as 0.5. Results: Logistic Regression prediction appears to be better accuracy of 95% than SVM, KNN, Decision Tree, and Random Forest of 92%, 90%, 85%, 91%. Significance of this proposed system is likely to be 0.55. Conclusion: In this study, it is found that Logistic Regression appears to be better than the SVM, KNN, Decision Tree, and Random Forest in breast cancer detection using the Wisconsin dataset.
Linear Regression Algorithm Based Price Prediction of Car and Accuracy Comparison with Support Vector Machine Algorithm
Authors: Siva Ramgiri , M Adimoolam
Published: April 2022

The aim of the study is to use Linear Regression (LR) algorithm based price prediction of car price and accuracy comparison with support vector machine (SVM) classification algorithm. Materials and methods: LR (N=205) and SVM algorithm (N=205) are applied for car price prediction as a mechanism. The accuracy and prediction of the classifiers was evaluated and recorded with G power 80% and alpha value 0.05. Results: The SVM produces 89% accuracy in predicting the car price on the sample dataset and the LR predicts the accuracy at the rate 91.7%. LR algorithm based accuracy appears (significant 0.563) to be better than SVM algorithm for car price prediction. Conclusion: The accuracy performance parameter of the LR algorithm appears to be better than the SVM algorithm.
Role of Content Marketing as a Sustainable Business Strategy
Authors: Shakya Prachi Basu , Sinha Prachi , Nair Priya Prateesh , Rao Sanjay Rama , Banerjee T
Published: April 2022

To understand the impact of content marketing in the digital media on the effectiveness of marketing so that it can be used as a sustainable business strategy. Approach: This is a review paper which exhaustively studies previously published research on the topic. It gives an overview as to how content marketing can be utilized as a sustainability tool in businesses. Findings: Through an exhaustive review of literature, it was observed that there is a positive linkage between content marketing strategy and cost reduction, resource efficiency, customer attraction, competitive advantage, and brand building. Practical implications: The paper suggests how content marketing brings sustainability to any business. Value: While talking about sustainability in business, the paper stresses upon the business value and not just the monetary value of any business.
Redox Mediated Neutral Electrolyte Solution for High Performing Ni(OH)2-MnO2-Rgo Supercapacitor Electrode
Authors: Tarek Yeasin Arafat , Shakil Ragib , Kumar Roy Chanchal , Firoz Shakhawat H.
Published: April 2022

Using a redox-mediated neutral electrolytic system (0.5 M Na2SO4+ 0.5 M K4FeCN6), a ternary hybrid of Ni(OH)2-MnO2-rGO as a supercapacitor electrode was investigated. The hybrid electrode was synthesized by adopting a simple hydrothermal approach. The phase of the α-Ni(OH)2 and γ-MnO2 was confirmed by X-ray Diffraction (XRD), as well their incorporation was observed by High-resolution transmission electron microscopy (HRTEM). The hybrid electrode in the redox system has demonstrated appealing performance due to the improved charge transfer capability of redox-active K4FeCN6, and hence, a high specific capacitance of 870 Fg-1
was found within the potential window of 0-1.0 V at 1 Ag-1
current density. As well, a high energy density of 30.2 Whkg-1
was found by using a symmetrical two-electrode setup. On top even after 5000 cycles, this supercapacitor has shown 92% of capacitance retention while maintaining 95% Coulombic efficiency. From a comparative perspective, the electrode was also tested on neutral Na2SO4, KOH, and H2SO4 electrolytes.
Design and Implementation of Level Control Management: Level Manager
Authors: Divya Sravani Bandi , Vishal Reddy C , Chaithanya J. Krishna
Published: April 2022

Water is one of the basic needs of all living beings. Wastage of water is one of the most significant reasons for water shortage around the world. At the household level, overflow of water from the overhead tanks may happen without our knowledge. Hence to prevent this and to save water at least for a certain extent, implementation of an automatic water level manager can be a solution. Significance of the proposed system is that the device can detect the level of water in the overhead tank and according to the level of water, the motor pump is switched on/off automatically by Arduino. Level of water in the sump can also be monitored. The information is sent to the controller for a decision whether water has to be pumped to the overhead tank. Additionally, the system senses continuous flow of water, if present, as possible leakage and issues alarm.
Determination of Hydrocarbon Contaminated Soil Properties and Behaviour as Predicted by Critical State Model
Authors: Srivastava Shubham , Verma Deepti , Paramkusam Bala Ramudu , Kumar Rajesh
Published: April 2022

The petroleum industry effluents and oil spills cause a serious threat to the ecology and to the soil properties leaving it to be of limited and no use. Bioremediation is done for such hydrocarbon contaminated soils. However, for determining their alternative usage in reference to construction industry, it is essential to analyze their properties. In this study, hydrocarbon contaminated soil properties were determined by triaxial tests under consolidated drained and consolidated undrained condition for both normally consolidated and over consolidated soil in conjunction with the soil behaviour as predicted by the critical state model. Due to the tension between the hydrocarbon in the pores of soil and water, complete saturation could not be achieved and the sample also disintegrated upon application of back pressure. Under near saturation condition the tests were performed, however, the contaminated soil didn’t not show soil softening even in case of over consolidated soils.
Novel Diagnostic System for COVID-19 Pneumonia Using Forward Propagation of Convolutional Neural Network Comparing with Artificial Neural Network
Authors: Prudhvi Kumar B. , TP Anithaashri
Published: April 2022

To enhance the poor diagnosing system for detecting COVID pneumonia using AI and to compare the algorithms and their performances in diagnosis prediction. Materials and methods: The technique of Convolutional Neural Network (CNN) with forward propagation for the feature extraction from X-ray images of patients diagnosis. The implementation has been carried out with the help of Tensorflow and Keras. The algorithms tested over 700 sets of chest X-ray images which has been utilized for test and train dataset images respectively, that are user chest X-rays classified and predicted with the novel diagnosis. Result: The analysis on the dataset and test cases has been performed successfully and acquired 91% accuracy for the CNN with forward propagation algorithm and compared to the artificial neural network algorithm (ANN), which gave 73% accuracy. With the level of significance (p<0.005), the resultant data depicts the reliability in independent sample t tests. Conclusion: On the whole process of prediction of accuracy for the image recognition through the CNN with forward propagation gives significantly better performance when compared to ANN.
Technology Integrated Inclusive Learning Spaces for Industry 4.0 Adaptive Learners- Lur Model for Sustainable Competency Development
Authors: Ghosh Nitu , Ayer Bharti , Sharma Ruchika
Published: April 2022

Goal of learning in this millennium is to create an inclusive learning environment for all. Inclusivity in the millennial age learning environment (referred to as Learning 4.0 age) is achieved through the integration of technology and learning accessed by masses in a standardized, indiscriminate, self-paced, affordable, and technologically friendly form, while also instilling in the learners with the skills required by Industry 4.0. To fully realize Industry 4.0's potential, organizations will need to take a more creative, inclusive approach to talent development and some deliberate unlearning of outdated approaches and learning of new ones. Thus, this study focuses on the Unlearning-Relearning (LUR) model to bridge the gap between Industry-academia 4.0 and fill the skill gaps. The study highlights the need to create technology-integrated inclusive learning spaces for millennials as per the industry 4.0 requirements by proposing an 'Unlearn-Relearn Model', which incorporates advanced technology and the unlearning-relearning concept and strong feedback loop to achieve its purpose of sustainable competency development.
Hybrid Model for Detection of Corrosion in Water Pipeline Images Using CNN and Comparing Accuracy with SVM
Authors: O Naveen kumar reddy , G Ramkumar
Published: April 2022

The work aims at studying a hybrid model for novel corrosion detection in water pipeline images using two different machine learning algorithms in low resolution images. Methods and Material: Convolutional Neural Network (CNN) and Support Vector Machine (SVM) algorithm implemented to detect the corrosion in low resolution image dataset with 40 samples. Results: CNN Classifier model has an detection accuracy value of 93.18% and the SVM has an detection accuracy of 77.77%. Attained significance (p=0.001) through SPSS tool. Conclusion: CNN algorithm perform well compared to SVM algorithm.
Intensify Cloud Security and Privacy Against Phishing Attacks
Authors: Prasad Vivek Kumar , Dansana Debabrata , Mishra Brojo Kishore , Bhavsar Madhuri
Published: April 2022

The world of computation has shifted from centralized (client-server, not web-based) to distributed systems during the last three decades. We are now reverting to virtual centralization, i.e., Cloud Computing (CC). In the world of computation, the location of data and processes makes all the difference. A person has complete control over the data and operations in their computer. On the other side, CC involves a vendor providing service and data upkeep. At the same time, the client/customer is ignorant of where the processes are operating or where the data is kept. As a result, the client does not influence it and doesn't have the right to do it. When it comes to data security in cloud computing, the vendor must guarantee service level agreements (SLAs) to persuade the client. As a result, the SLA must define several degrees of security and their complexity depending on the benefits for the client to comprehend the security rules in place. Phishing is a social engineering assault that is frequently used to obtain user information, such as login passwords and credit card details. It happens when an attacker poses as a trustworthy entity and tricks the victim into opening an e-mail, instant message, or text message. In this research paper, the methodology that tries to identify the phishing attack in the cloud eco-system has been explored and mentioned. The approach used here classifies the malicious and non-malicious URLs.