bluuebunny/crossref_metadata_2025 huggingface dataset:
Single Stage Autonomous Solar Water Pumping System Using PI and Fuzzy Controllers
Authors: Harikrishnareddy Bujula
Published: August 2021

Sustainable powerage and viable use of accessible energy assets have arisen as an commendable panacea for expanding carbon impression, draining petroleum derivatives, expanding a dangerous atmospheric deviation and changing meteorological situations. Flawless nature, silent activity and bountiful accessibility even at distant areas, have made the sunlight based energy finest form of RE accessible in the current situation .The work presents a introverted stage independent sun oriented photovoltaic exhibit take care of water siphoning framework utilizing a long-lasting magnet simultaneous engine. The crucial commitment of this work incorporates advancement of novel altered vector control, which improves the force reaction of the framework and improvement of a novel single stage variable advance size gradual conductance strategy, which gives a quick greatest force point following and dispenses with the need of transitional stage DC-DC converter. A corresponding indispensable control diminishes the mistake among reference and real value. The utilization of single stage geography has killed middle stage DC-DC converter and diminished the quantity of components, consequently bringing about decrease of the expense, intricacy and increment efficiency .The expansion of this activities rather than PI regulators that we need to Fuzzy and PI regulators .Utilizing this controllers step reaction of speed increases, Dc-connect voltage increases and force speed proportion is all the more then, at that point power stream will be improved. The framework execution has been examined through Matlab /simulink recreation investigation
Simulation Analysis of Circuit and Designing of PCB Layout of a CMOS based NAND Logic Gate using Open-Source Software eSim
Authors: Tanwar Vanshika
Published: August 2021

A real world signals are mostly based on Boolean operators. In simple language Boolean operators are logic gates and logic gates are the building blocks of any circuit. There are different types of logic gates like AND, OR, NOT, NAND, NOR, XOR, and XNOR. These all-logic gates are implemented using a Boolean function. And all these logic gates internally are implemented using diodes and transistors. And when we implement all these logic gates using transistor and diodes then it comes under logic families. In this paper we are going to do the analysis of NAND GATE using CMOS in 180 nm technology and has also designed its PCB layout. We are going to carried out the whole simulation of the proposed design of NAND Gate in eSim (Electronic Simulation) Software which is an EDA tool. And by changing the different values of inputs of NAND Gate we are observing respective output in simulation process of eSim.
Electric Vehicle and its Types
Authors: Tripathi P. M.
Published: August 2021

Electric vehicles are an important option for reducing greenhouse gas emissions. Electric vehicles not only reduce dependence on fossil fuels, but also reduce the impact of ozone-depleting substances and promote widespread adoption of renewable energies. Despite extensive research into the properties and characteristics of electric vehicles as well as the nature of their charging infrastructure, electric vehicle construction and grid modeling continue to evolve and become limited. regime. This paper presents market penetration surveys for electric vehicles, hybrid electric vehicles, plug-in hybrid electric vehicles and battery electric vehicles, and describes optimal engineering and modeling approaches. their differences. Research on critical barriers and inadequate charging equipment targets developing countries like India, which makes the study unique. The development of the new Vehicle to Grid concept has created additional energy sources when renewable energy sources are not available. We conclude that considering the specific characteristics of an electric vehicle is important in the mobility of the electric vehicle.
Behavioral Based Credit Card Fraud Detection
Authors: S Shalini
Published: August 2021

Credit card fraud is a significant threat in the BFSI sector. This credit card fraud detection system analyzes user behavioral patterns and their location to identify any unusual patterns. This consists of user characteristics, which includes user spending styles as well as standard user geographic places to verify his identity. One of the user behavior patterns includes spending habits, usage patterns, etc. This system deals with user credit card data for various characteristics, which includes user country, usual spending procedures. Based upon previous transactions information of that person, the system recognizes unusual patterns in the payment method. The fraud detection system contains the past transaction data of each user. Based on this data, it identifies the standard user behavior patterns for individual users, and any deviation from those normal user patterns becomes a trigger for the detection system. If it detects any unusual patterns, then user will be required to undergo the security verification, which identifies the original user using QR code recognition system. In case of any unusual activity, the system not only raises alerts but it will block the user after three invalid attempts.
Analysis of Image Processing and Its Challenges
Authors: Kanavi Vijayamahantesh
Published: August 2021

Major two main areas of application. Improved visual information for human interpretation. Process image data for memory, transmission and representation for the perception of automata. The purpose of this article is to define the meaning and scope of image processing, describe the various steps and methodologies involved in typical image processing and the application of image processing tools and procedures
A Transformer less Buck Boost Converter with Positive Output Voltage
Authors: Reddy Lambu Rushi
Published: August 2021

Some industrial applications require high step-up and step-down voltage gain. The transformer less buck-boost converter has high voltage gain than that of traditional buck-boost converter without extreme duty cycles. A transformer less buck-boost converter with simple structure is obtained by inserting an additional switched network into the traditional buck-boost converter. The two power switches of the buck-boost converter operate synchronously. The operating principles of the buck-boost converter operating in continuous conduction modes are presented. A new buck- boost converter is presented by providing a feedback to the converter. By this, constant output voltage can be maintained under varying load conditions in both buck and boost operation. The output voltage of 40V (step—up mode)/8V (step down mode) is obtained with input voltage 18V and the outcomes are approved through recreation using PSIM MODEL.
Research on Survey for Finding Effects of Covid-19 Pandemic on Construction Industry
Authors: Sonak Samiksha P.
Published: August 2021

This research paper is mainly carrying purpose of finding the effects of Covid-19 pandemic on construction industry. This is achieved through a methodology which involved online questionnaire survey based on the quantitative assessment of the impacts as well as review of the professionals who are the respondents. The respondents are directly related to construction activities and also possess good credibility for their work and academic qualification. The survey has been designed and hosted via google forms and shared with respondents mentioned earlier. The survey is designed so as the researcher gets insights related to even minute problems which were faced by the professionals during the hard times of pandemic. Survey is also taking care of gathering information related to probable losses caused to the respondents by asking an open-ended question related to work. Further the gathered data has been explained theoretically as well as represented visually by bar graphs and pie charts etc. From obtained results, a badly affected conditions pf construction industry come in light. Majority of respondents were forced to fully or partially stop their projects. Other issues which are highlighted by more than one third of the respondents are, higher operating cost at site, decreased demand of construction during Covid-19, supply chain provider’s problem, black marketing. Actual number of affected professionals is a dark side in such difficult time. Keywords: Professionals, business, experience, data, questionnaire survey, black
Micropropagation of Rose (Rosa Hybrida) Using Invitro Technique by Natural Hormone
Authors: R Visvanand.
Published: August 2021

In recent years ,several Micropropagation technique has been established, to make some improved method of crop yield production the natural hormone from other plant species were selected for the beneficial result in the plant species. The Micro propagation technique is carried out in Rosa hybrida explant by providing the different natural shooting and rooting hormone in three different compositions with the half strength of MS medium , it is to predict the ability of which natural hormone is being utilized by the nodal explant of Rosa hybrida. The three different natural shooting and rooting hormone are Aloe vera gel extract and the tender coconut water with 50 ml and 100 ml and 150 ml of concentration in half strength MS media and the Cinnamon powder alone taken in the .5 g,1g and 1.5 g of concentration in half strength MS media due to the powdery form. These were proceeded in aseptic condition of propagation as a result it has been noticed that among the three natural hormone the remarkable growth has been found in the tender coconut water provided nodal segment in all the three concentration .This article has a goal to promote the use of the natural rooting role in the plant breeding industry.
Comparative Study of Conventional Steel Braces and Buckling Restrained Braces in a High-Rise RC Building
Authors: Kumar K Nanda
Published: August 2021

A study was carried out on a reinforced concrete building with conventional steel braces and buckling restrained braces (BRB) for seismic analysis with dissimilar type of bracing system ( V type, inverted V type, X type, Zig-Zag bracing) is considered. The bracing is providing for outer exterior columns. A twenty-five storey (G+25) building is located at earthquake zone 2 & 4. The structure models are examined by response spectrum method using ETABS2016 program. The parameters which are consider in this research to equate the seismic investigation of buildings are storey displacement, storey drift, storey shear(forces). These parameters are compared in both type of bracing systems and effective bracing is selected with respect to different zones.
Lapdock: Brainless Laptop
Authors: Prajapati Shivam
Published: August 2021

Lapdock is based on the idea of providing a variation to our typical laptops and making them more efficient and comfortable to use. It is made up of two words mainly: - lap (seated person’s upper leg) and dock (plug or anchor) [1]. Lapdocks do not contain CPU of their own and this makes them different from laptops despite their similar appearance. The good thing about lapdocks is that lapdocks do not store any data in them. The devices are powered by using other devices that come with embedded O.S. For example: - Android phones, Raspberry pi etc. As these lapdocks do not contain any fragile part such as CPU or HDDs, it adds to its durability. All you need to do is to connect your intelligent devices to lapdock using a cable such as an HDMI cable and the lapdock is ready to be used. A lapdock is not a typical appliance, but it is the ultimate device and future of laptops. On an average, it is quite rare to change our laptops frequently. Laptops are expensive devices and require a lot of software to be downloaded while purchasing them. For their proper functioning, the software needs to be updated on a regular basis. Along with this, the other devices such as your phones and cameras are also needed to be updated accordingly. Using lapdocks we can get rid of tedious and costly tasks by updating just one device and using it to do our work. It is quite usual for people to change their mobile phones frequently as new and advanced features are launched in the market. With auto update it is easier to keep your phones updated than to update or change your laptop. There can be numerous reasons to change your phones: - phones become slower, crash, the bater might deplete fast, the camera becomes outdated and so on. People require new phones, whether for a new feature, technological development, or merely to modify. So, getting the latest phone is quite common and hence lapdocks are a better option. These devices are durable and need no applications. Infact, they do not require any other technical support so they need not be upgraded or replaced on a regular basis. That is why lapdocks are indeed the future and a workable alternative to owning a single long-lasting item and as a result avoiding obsolete electronic waste.
The Impact of Internal Mobility Policies on Employee Performance at Private Banks Mysore
Authors: T J Ramya
Published: August 2021

The banking industry has tremendous growth in Indian market .The entrance of new policies in banking sector has bought changes in employee performance. Retaining employees in private banks has lot of challenges. Employee retention and employee performance is a contemporary approach for the development of private banks. The private banks has initiated news ways to implement internal mobility policies to retain employees . This paper presents an novel employee internal mobility survey in the private banks in Mysore . The research study is based on the following criteria, internal mobility policies, employee satisfaction towards internal mobility, factors influencing employee satisfaction, internal mobility policies towards employees’ retention. The target population for the study is employees of private banks .Required analysis will be done to measure the impact of internal mobility on employee performance. The current study focuses on impact of internal mobility on employee performance in the organization, and also the factors which has impact on internal mobility policies on employee performance. For the persistence of study primary data and secondary data is used. The research results impact of internal mobility on employee performance in private banks Mysore.
Preparation of PP/PP-g-MAH/C15A Nanocomposite by Melt Extrusion Process and Comparative Study of its Mechanical and Non-Isothermal Crystallization Behaviour
Authors: Sahoo Rajesh Kumar
Published: August 2021

Nanocomposite films have been prepared by melt blending method with the help of twin screw extruder using polymer polypropylene(PP)nucleating agent like organically modified nanoclay at optimum loading condition. Compatibilizers such as polypropylene grafted maleic anhydride (PP-g-MAH) were used for better compatibility between polymer matrix and filler. The effect of organoclay on nucleation effect and subsequent incremental values in mechanical and thermal behavior of different nanocomposite films has been investigated and explained with justifications. The tensile properties have shown to be improved in presence of clay nanoparticles due to resistance exerted by clay layers against plastic deformation of the polymer. Thermal properties measured by differential scanning calorimeter shows increased crystallization temperature of the nanocomposites in presence of clay particles and compatibilizer of optimum concentration.
Future Trend Prediction in Share Market with Machine Learning
Authors: Mahajan Prof. Kanchan
Published: August 2021

In Stock Market Prediction, the point is to estimate the future worth of the monetary loads of an organization. The new pattern in securities exchange forecast advances is the utilization of AI which makes expectations dependent on the upsides of current financial exchange lists via preparing on their past qualities. AI itself utilizes various models to make expectation simpler and credible. The thought centers on the utilization of dissimilar Machine learning algorithms to anticipate stock qualities. Variables considered are open, close, low, high and volume. The principal thing we have considered is the dataset of the securities exchange costs from earlier year. The dataset was pre-handled and adjusted for genuine examination. What's more, the proposed thought inspects the utilization of the forecast framework in verifiable settings and issues related with the accuracy of the general qualities given. The thought additionally portrays AI model to foresee the life span of the stock in a serious market. The effective forecast of the stock will be an extraordinary resource for the securities exchange establishments and will give genuine answers for the issues that stock financial backers face.
E-Pharma System
Authors: Bajaj Hrithik
Published: August 2021

The primary goal of this program's development is to deliver all medical-related solutions in a single web application. E-Pharma is a platform that allows patients and doctors to communicate directly with one another. Direct doctor-patient relationships, consumer familiarity with online purchases, the simplicity of mail-order trading, and distance marketing can all help patients self-diagnose. The patient can speak with the doctor and ask questions.
Comparison of Analytical and Software Based Design of Energy Efficient Induction Motor
Authors: Kishore Sai
Published: August 2021

Energy Efficient Induction motor is playing a vital role in current scenario. Due to rising electrical energy demand, increased awareness of global warming, and rising fossil fuel prices, energy efficiency has become increasingly important. Apart from adding capacity, the only practical approach to deal with this situation is to make optimal use of the available energy, which may be done by using energy efficient Motors. The main objective of this paper is to calculate and Compare the Analytical and Electromagnetic Software based design for a 5HP Energy Efficient Motor.
Review on Thermal Analysis of Automobile Radiator
Authors: Kushwah Pavan
Published: August 2021

Radiators are used to transfer thermal energy from one medium to another for the purpose of cooling. Low efficiency heat exchangers used in automotive as radiator may cause to serious dangers for the engine. Hence, thermal scientists and engineers always pursuit modern methods to enhance the heat removal of the engine. It seems nanofluids implementation in automotive cooling system promises to achieve high efficiency radiators. This paper reviews almost all performed studies in this area that are available in the literature. Author collects details about nanoparticles materials and size, base fluid, volume, concentration, flow regime and Reynolds number used in studies. Usually, maximum heat transfer enhancement and maximum need of pumping power that occurs at the highest volumetric concentration of nanoparticles, simultaneously. On the other hand, using nanofluids, due to the enhanced heat carrying capacity of the nanofluids; the pumping power required will also be reduced.
MPPT-Based Single Phase Solar String Inverter
Authors: Arundhathi Pervala
Published: August 2021

A microcontroller primarily based totally method of producing a sine wave from the sun panel output is designed and carried out on this paper the usage of a two-degree topology for a sun string inverter. This paper offers the improvement of a most energy factor tracking (MPPT) and manipulate circuit for a unmarried section inverter the usage of a pulse width modulation (PWM) IC. The elegance of this configuration is the removal of a complicated circuitry to generate oscillation pulses for transistor switches. The controller IC TL494 is capable of generate the vital waveforms to manipulate the frequency of inverter via right use of switching pulse. The DC to AC inversion is correctly completed along the switching signals; the circuit produced inverter output of frequency almost 50 Hz. The major goal of the proposed method is to layout a low cost, low harmonics voltage supply inverter basically targeted upon low energy digital home equipment the usage of variable sun energy as inputs.
A Research Paper on Convolutional Neural Network (CNN) Theory based Automated Traffic and Road Sign Detection and Recognition System
Authors: J. Parkavi
Published: August 2021

India is a country with a dense road network and has a complex system to maintain road safety. As we all know that we have a complex traffic system in which we have more than 100 types of traffic symbols in it. While driving, it is tough to take care of all the symbols placed at the road end. Sometimes the driver does not know what that symbol says. In this system sometimes the driver misses the road signs because the attention of the driver is overdriving the vehicle safe which leads to an accident or issuing Challan. Sometimes the traffic signs don't notice by the driver. So all the drivers or the vehicle need a system which is capable to read and recognize the traffic symbol placed at the road end and the system must be capable of giving simple instruction to the driver. So that system can automatically detect which type of symbol is this and can notify the driver. The system must have a good accuracy rate, as well as the system, must have a very good speed of working. This system can also be used in driverless cars to notify the system about the road signals and hence the system can tackle all the symbols carefully.
Automated Brain Tumor Prediction System using Natural Language Processing (NLP)
Authors: Sharma Gourav
Published: August 2021

In this paper, we proposed an Automated Brain Tumor Prediction System which predicts Brain Tumor through symptoms in several diseases using Natural Language Processing (NLP). Term Frequency Inverse Document Frequency (TF-IDF) is used for calculating term weighting of terms on different disease’s symptoms. Cosine Similarity Measure and Euclidean Distance are used for calculating angular and linear distance respectively between diseases and symptoms for getting ranking of the Brain Tumor in the ranked diseases. A novel mathematical strategy is used here for predicting chance of Brain Tumor through symptoms in several diseases. According to the proposed novel mathematical strategy, the chance of the Brain Tumor is proportional to the obtained similarity value of the Brain Tumor when symptoms are queried and inversely proportional to the rank of the Brain Tumor in several diseases and the maximum similarity value of the Brain Tumor, where all symptoms of Brain Tumor are present.
Human Papillomavirus Targeted Immunotherapy Outcome Prediction Using Machine Learning
Authors: Moni Vidya
Published: August 2021

Warts caused by the Human Papillomavirus (HPV) is a highly contagious disease, and affects several million people across the globe every year, in the form of small lesions on the skin, commonly known as warts. Warts can be treated effectively with several methods, the most effective being Immunotherapy and Cryotherapy. Our research is focused on the performance comparison of modern Machine Learning classification techniques to predict the outcome (positive or negative) of Immunotherapy treatment given to a patient, by using patient data as input features to our classifiers. The precision, recall, f-measure and accuracy were used to compare the performance of the various classifiers considered in this study. We considered Logistic Regression, ZeroR, AdaBoost, K-Nearest Neighbours (KNN), Support Vector Machines (SVM), Gradient Boosting, Repeated Incremental Pruning to Produce Error Reduction (RIPPER), Decision Trees and Random Forests. The ZeroR classifier was used as a baseline to provide us with insights into the skewed nature of the data, so as to enable us to better understand the comparison in performance of the various classifiers.
Retinal Vessel Analysis for Detection of Glaucoma
Authors: R Chandana
Published: August 2021

Glaucoma, a disease of the optic nerve is caused by the increase in the intraocular pressure of the eye and results in damage to the optic nerve and vision loss. The main characteristic of glaucoma is an elevated intraocular pressure (IOP) and also the blood vessels get narrower. Vessel segmentation is one of the main steps in retinal automated analysis tools. Retinal vessel segmentation and delineation of morphological attributes of retinal blood vessels are utilized for diagnosis, screening, treatment, and evaluation of various cardiovascular and ophthalmologic diseases. Since, the numbers of blood vessels are more in the glaucomatous eye , glaucoma is detected by means of ISNT ratio. The image processing operations are performed on glaucomatous and normal eyes. We have chosen ten images of each from the database and ISNT ratio is calculated to get the area of blood vessels in each of the four quadrants of the eye and hence glaucoma is detected.
Credit Card Fraud Detection using Machine Learning and Data Science
Authors: . Aman
Published: August 2021

It is important that companies are able to identify fraudulent credit card transactions so that customers are not charged for items that they did not purchase. These problems can be handled with Data Science and its importance, along with Machine Learning. This project aim is to illustrate the modelling of a data set using machine learning with Credit Card. Our objective is to detect 100% of the fraudulent transactions while minimizing the incorrect fraud classifications. Credit Card Fraud Detection is a sample of classification. In this process, we have focused on analysing and pre-processing data sets as well as the deployment of multiple anomaly detection algorithms such as Local Outlier Factor and Isolation Forest algorithm on the PCA transformed Credit Card Transaction data.
Opinion Mining of Amazon Data for Alexa Review Analysis
Authors: Gautam Neetima
Published: August 2021

The fast expansion in piles of unstructured literary information joined by multiplication of devices to investigate them has opened up extraordinary freedoms and difficulties for text mining research. The programmed naming of information is hard in light of the fact that individuals regularly express feelings in complex manners that are here and there hard to fathom. The marking interaction includes tremendous measure of endeavours and mislabelled datasets typically lead to erroneous choices. In this paper, we plan a frame work for sentiment analysis with opinion mining for the instance of Amazon Alexa. Most accessible datasets are not named which presents a great deal of works for scientists as tolls text information pre-preparing task is concerned. Also, supposition datasets are frequently profoundly area touchy and difficult to make since assumptions are sentiments like feelings, mentalities and conclusions that are ordinarily overflowing with phrases, sound to word imitations, homophones, phonemes, similar sounding word usages and abbreviations. The proposed system is named feeling extremity that naturally readies a supposition dataset for preparing and testing to extricate impartial assessments of inn administrations from surveys to find a reasonable AI calculation for the grouping segment of the structure.
Modelling and Life Cycle Assessment of Sewage Treatment Plant (STP) in Lucknow City
Authors: Gole Narendra Pal
Published: August 2021

The implementation of wastewater treatment plants has been a challenge for most countries. Economic resources, political will, institutional strength, and cultural background are important factors that define the trajectory of pollution control in many countries. Technology is sometimes mentioned as one of the reasons hindering further development. Therefore, a key objective of this research is to evaluate the performance of a plant based on the 345 MLD Upflow Anaerobic Sludge Blanket (UASB) technology by analyzing the physical and chemical parameters of the water treated by UASB to evaluate the performance of the plant located. at Bharwara Tech from Gomti Nagar Lucknow. In this study, the performance of the wastewater treatment plant and the UASB reactor was calculated. Wastewater is mixed with domestic wastewater, so the concentration of BOD and COD is relatively low. The amount of biogas produced by the UASB reactor is also less than its design value. All STP inlet and outlet water concentration results are displayed graphically.
A Review on Automatic Covid-19 Lung Infection Detection from Different Imaging Techniques
Authors: Singh Sangeeta
Published: August 2021

Corona Virus Disease-2019 commonly known as COVID-19 which has been defined by the Novel Corona Virus. It is a family of severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) and was first detected during respiratory outbreak. It was first reported to the World Health Organization on December 31, 2019. On January 30, 2020, the World Health Organization declared the COVID-19 eruption a global health emergency. As of 27-May-2021 169,095,283 confirmed cases have been reported in the world and 2, 73, 67, 935 cases in India. It is required to identify the infection with high precision rate but there are lots of deficiency in the diagnosing system that may resulted false alarm rate. Initially it could be detected through throat saliva but now it can also be identified thought the impairment in lungs from computerized tomographical imaging technique. This paper reviewed various researches over COVID-19 diagnosis approach as well as the syndrome in respiratory organs. There are so many imaging techniques through which lungs impairments can be detected that may diagnose COVID-19 with high level of accuracy. CT scan image is the best alternative for diagnosing COVID-19.
The Efficiency of Natural Adsorbents to Remove Fluoride from Drinking Water: A Review
Authors: Marad Aishwarya P
Published: August 2021

Widespread existence of fluoride above the desirable limit in ground water, reported that 17 states of India are facing endemic fluorosis problem. Excess amount of fluoride is being emitted due to increase in human activities. Businesses release effluents exceptionally stacked with fluoride. The over abundance of fluoride is destructive from numerous points of view this there is a need to cut down the fluoride level to the safe limits. For this reason the treatment of water is done using number of techniques like coagulation and flocculation, ion-exchange, electrochemical methods, nano filtration, adsorption etc. Adsorption is a significant process in which the fluoride is adsorbed on to a membrane or fixed bed. Activated carbon is a commonly used adsorbent for water and waste water treatment, but the main disadvantage of the activated carbon is the cost and rejuvenation difficulty. Many attempts are done to defluoride water from high concentration to permissible level, still the studies are going on to implement a user friendly defluoridation methods using low cost, sufficiently available and highly effective adsorbent.
Audio Classification for Noise Filtering Using Convolutional Neural Network Approach
Authors: Sudheer D.
Published: August 2021

In each part of daily routine, sound assumes a significant part. From discrete security features to basic reconnaissance, a sound is a vivacious component to create automated frameworks for these fields. Scarcely any frameworks are now on the lookout, yet their effectiveness is a concerned point for their execution, real-time conditions. The learning capacities of Deep learning designs can be utilized to create sound characterization frameworks increase the impact of sound classification. Our main aim in this paper is to implement deep learning networks for filtering the nose and arrangement of these sound created by the natural phenomenon’s according to the spectrograms that are created accordingly. The spectrograms of these natural sounds are utilized for the preparation of the Convolutional neural network (CNN) and Tensor Deep Stacking Network (TDSN). The utilized datasets for analysis and creation of the networks are ESC-10 and ESC-50. These frameworks produced from these datasets were efficient in accomplishment of filtering the audio and recognizing the audio of the natural sound. The precision obtained from the developed system is 80% for CNN and 70% for TDSN. Form the implemented framework, it is presumed that proposed approach for sound filtering and recognition through the utility spectrogram of their subsequent sounds can be productively used to create efficient frameworks for audio classification and recognition based on neural networks.
Comparison of SRF and IRPT Algorithm for Mitigation of Voltage Sag and Voltage Swell using NPC based D-STATCOM
Authors: Lokhande Rushikesh
Published: August 2021

This study describes a systematic model of Distribution STATCOM (D-STATCOM) to reduce voltage sag, and swell using Instantaneous reactive power theory also called Power Quality theory (IRPT or PQ) and Synchronous reference frame theory (SRF) using NPC three level inverter. Power quality is an event that manifests as an abnormal frequency, current and voltage resulting in the failure of end-use equipment. The main issues addressed here are voltage sag and swell. Custom power devices are utilised to overcome this problem. The Distribution STATCOM (D-STATCOM) is one of these devices, and it is the most efficient and effective modern specialized power device utilised in distribution system network. The simulation of D-STATCOM is done using MATLAB/Simulink and voltage sag and swell are mitigated.
A Data Science Approach to Bioinformatics
Authors: Rakesh Palepu Narasimha
Published: August 2021

Computer aided drug design (CADD) which uses the computational advance towards to develop, discover and scrutinize and examine drugs and alike biologically agile molecules. CADD is a specialized stream which uses the computational techniques to mimic drug-receptor interactions. CADD procedures are so much dependent on the tools of bioinformatics, databases & applications. There are so many advantages of computer aided drug discovery; it saves lot of time which is one of the main advantages followed by low cost and more accuracy. CADD required less manpower to work. There are different types of CADD such as ligand and structure based design. Objectives of the Computer aided drug design are to boost up the screening process, to test the rational of drug design, to efficiently screen and to remove hopeless ones as early as possible. In Drug designing the selected molecule should be organic small molecule, complementary in shape to the target and oppositely charged to the biomolecular target. The molecule will interacts and binds with the target which activates or inhibits the function of a biomolecule such as a protein or lipid. The main basic goal in the drug design is to forecast whether a given molecule will bind to target and if thus how strongly. Molecular mechanics techniques also used to provide the semi quantitative prediction of the binding affinity. These techniques use machine learning, linear regression, neural nets or other statistical methods to derive predictive binding affinity equations. Preferably, the computational technique will be able to forecast the affinity prior to a compound is synthesized, saving huge time and cost. Computational techniques have quickened the discovery by decreasing the number of iterations required and have often produced the novel structures.
Web-based Fractional Ownership in Real Estate
Authors: Zinzuwadia Suraj
Published: August 2021

The Indian real estate sector is one of the fastest-growing sectors. Real estate crowdfunding is a way of raising money for real estate investment by reaching out to a pool of investors to contribute a small amount of money towards a project. Real estate crowdfunding can be achieved by fractional ownership. Fractional ownership splits the cost of expensive property among several people. As popular the concepts seem, it has not been implemented in some parts concerning the higher risk factor. Such a process is complex if the person is a beginner and has little idea about the same. The objective of this paper is to display the real estate properties and connect investors-owners using a web-based application system. This system also advises market patterns, value ranges, and enhancing the advancements of the future cost will be predicted through machine learning model.
Implementation of Bidirectional DC to DC Converter and Inverter for Vehicle to Grid System by using Sliding Mode and Fuzzy Logic Controller
Authors: Bembde Jayshree
Published: August 2021

In this paper a bidirectional DC to DC converter is designed by using sliding mode controller and fuzzy logic controller for vehicle to grid system. The vehicle to grid technique is intended to work in both grid to a vehicle battery and vehicle battery to grid applications in vehicle-to-grid scenarios. The two methodologies is verified using MATLAB software. Hardware is made by using a LAUNCHXL-F28377S microcontroller.
Improving Pronunciation for Non-Native Speakers Using Neural Networks
Authors: Santhoshi R
Published: August 2021

While learning a new language through the internet or applications, a lot of them focus on teaching words and sentences and do not concentrate on the pronouncing ability of the users. Even though many speakers are proficient in a language, their pronunciation might be influenced by their native language. For people who are interested in improving their pronunciation capabilities this proposed system was introduced. This system is primarily focused on improving the pronunciation of English words and sentences for non-native speakers i.e., for whom English is a second language. For a given audio clip, we scale the audio and extract the features, input the features to the model developed and the output of the model gives the phonemes that are spoken in the clip. Many models detect phonemes and various methods have been proposed but the main reason for choosing deep learning is that the learning and the features that we tend to oversee or overlook are picked up by the model provided the dataset is balanced and the model is built properly. The features to be considered varies for every speech processing project and through previous research work and through trial and error we choose the features that work best for us. Comparing the phonemes with the actual phonemes present, we can give the speaker which part of their speech they need to work on. Based on the phoneme, feedback is given on how to improve their pronunciation.
Super Resolution MRI Using Generative Adversarial Networks
Authors: . Gautam
Published: August 2021

This paper proposes a new frame for MRI Image Enhancement from a low-resolution (LR) image obtain from an early used MRI machine to generate a high-resolution (HR) MRI image. For this we use Generative Adversarial Networks, which have proven well in image recovery task. Here we simultaneously train two models which is Generative model that captures the data distribution in the LR MRI images, and a discriminative model that estimates the probability that a sample came from the training data rather than generator. For training generator, we have to maximize the probability of discriminator of making a mistake in comparing the fake image. For discriminator the adversarial loss uses least squares in order to stabilize the training and for generator the function is a combination of a least square adversarial loss and a content term based on mean square error and image gradient to improve the quality of generated images of MRI.
Near Duplicate Image Detection Using Image Net Model
Authors: B Anusha
Published: August 2021

The rapid development in the technology of Internet and the increase in the usage of mobile devices, it is very easy for users to capture, communicate and share the images through the networks. The spectacular achievement of convolution neural networks in the area of computer vision, will help us to match the features that are very similar between the images for detecting the duplicate version of the image. In this project we use Image Net model that mainly provide a large database that contains many images of different categories. Flask framework is used in this project, which includes many libraries, modules that helps the web developer to write web application. In this project the user is allowed to upload the image, then the image features will be extracted and fed to the CNN model. The CNN model will calculate the similarity distance between the images that is already present in the database and detect the top four images that are duplicate version of the uploaded image.
Knowledge and Perception toward Strabismus in Uttar Pradesh, India
Authors: Yadav Priti
Published: August 2021

Strabismus is a common eye condition having a potential subsequent impact on the psychological and socioeconomic domains of individuals suffering from strabismus. Therefore this study aimed to find out the level of knowledge and treatability of strabismus in Uttar Pradesh. Strabismus is the misaligned condition of eye. It is most likely to result in double vision and sometimes asthenopic symptoms. It is commonly called by different names; squint, crossed eyes, deviating eyes. AIM- To find out the level of knowledge and treatability of strabismus among adult people in Uttar Pradesh, India. METHODS- This is a cross sectional study that was conducted among adult people who live in U.P, India. By using an online self administered questionnaire. RESULT-Out of 57 participants, 40 .4% reported the correct definition of strabismus .the majority of responders agreed that strabismus is treatable (56.1%). In addition, a statically significant relation was found between knowledge of strabismus treatability and age, gender, work state , and level of education. Most participants were aware of the risk factors and complication of strabismus. Conclusion-Our study found that the majority of participants had good knowledge of the definition, treatment, and complications of untreated strabismus. Participant’s age, education level, work state incomes were the main factors found to be significantly associate with knowledge of strabismus treatment options.
Suitability of Scala
Authors: Gupta Vaishnavi
Published: August 2021

: We all are not new to the fact that data is increasing exponentially. It is increasing more than ever before, from 2 zetabytes in 2010 to 59 zetabytes in 2020. Not only this, it is predicted to be 149 zetabytes by 2024. As the data is growing and that too how the traditional methods like SQL, Excel, etc., would not be enough and feasible to analyze or store huge amount of data as they have storage and processing restrictions. It was important to use tools which are much more efficient and much more effective. To handle this ‘Big Data’ various tools were created E.g.: Hadoop, Spark, NoSQL, etc., not only this various programming languages also came into picture. Scala is just one of them. In this paper we are trying to highlight the importance of Scala, and how it is so unpopular and under-rated as compared to other programming languages; despite the fact that it is a strong statically typedgeneralpurpose programming language which supports both object oriented language and functional programming. Also, it is easy to understand and use as compared to other programming languages. In this paper we will see and discuss how Scala has been beneficial and why do we want it to gain more popularity in the industry. We will also see the cons associated and if it’s worthy enough given its cons.
Design of Linear Feedback Shift Register for Low Power Applications
Authors: Bhargavi K. Manju
Published: August 2021

This paper presents the design & implementation of the Linear Feedback Shift Register (LFSR) using the Mentor Graphics tool in 90nm technology. LFSR’s have a wide variety of applications. They are used in pseudo-random variety generation, whitening sequences and pseudo-noise sequences. MOS current-mode logic (MCML) and Dynamic current-mode logic (DYCML) are employed to design an LFSR. MCML is widely used in high-speed applications and these MCML circuits are based on current steering logic. The advantages of the MCML method are that they have high noise immunity due to their differential nature of inputs. The disadvantage of MCML approach is static power dissipation. To overcome these issues of MCML logic, Dynamic CML logic is used. Its advantages include low static power dissipation and high performance. This paper shows the comparison results of CMOS, Dynamic CML and MCML designs in terms of delay, power and transistor count.
Square Monopole Microstrip Antenna for Quad Band Operation
Authors: Patne Basawaraj
Published: August 2021

In this paper the square monopole microstrip antenna with slot on the radiating patch is presented for multiband operation. The antenna has a volume of 80×80×16 mm3. The antenna is fabricated using the modified glass epoxy substrate material. The antenna operates between the frequency range of 2.9 GHz to 10.87 GHz. The radiation characteristic is broadside and the peak gain of about 5.1dB is obtained in its operating frequency. The design details are tabulated and the results are presented and discussed. This antenna may find its applications in WLAN and Wi-max communication applications.
Raspberry Pi based Object Detection and Text Reader using Voice Assistance
Authors: M Sushmitha
Published: August 2021

Communication is the basic requirement for humans to connect and it requires text and speech but visually impaired people cannot able to perform this. This project helps them to read the image. This project is an automatic document reader for visually impaired people, developed on the Raspberry Pi processor board. It controls the peripherals like a camera, a speaker which acts as an interface between the system and the user. Here, we use a raspberry pi camera which is used to capture the image and scan the image using Image Magick software. Then the output of the scanned image is given to OCR(optical character recognition) software to convert the image to text. It converts the typed or printed text to the machine code. Then we use Text to Speech (TTS), which is used to convert speech to text. The experimental result is very helpful to blind people as there was much analysis of the different objects.
A Study of Sustainable Development Regarding to Value Education
Authors: Raheesh Ram
Published: August 2021

Development is very important for human life. It is very necessary for civilization also but it should be sustainable and welfarist for all organisms. This research paper focused on how to achieve sustainable development through value education, why values so important for sustainable development & how to give values education for sustainable development. The researcher completed 14 days refresher course on sustainable development, during this period listened many resource parsons with great knowledge on various aspect of sustainable development and read many books, reports, articles/papers on sustainable development and reached this conclusion that sustainable development cannot be achieved without values.