The 100 most-cited articles in International Journal for Research in Applied Science and Engineering Technology, 2021

Abstract: In the analysis of structures subjected to earthquake forces, it is usually assumed that the structure is fixed at the base to simplify the mathematical problem. This assumption leads to gross error in assessment of overall response under dynamic loads. The interaction phenomenon is principally affected by the mechanism of energy exchanged between the soil and the structure during an earthquake. In the present investigation, a multi-storied building which is located in Amaravati is chosen as the study area which consists of different types of soil / rock profiles at different locations. Many high rise structures are expected in future in the new city. Earthquake analysis is carried out when similar structure rests on different types of soils and the results of fundamental time periods, base shears and displacements are compared with the results obtained from fixed base condition.

Abstract: Deep learning's breakthrough in the field of artificial intelligence has resulted in the creation of a slew of deep learning models. One of these is the Generative Adversarial Network, which has only recently emerged. The goal of GAN is to use unsupervised learning to analyse the distribution of data and create more accurate results. The GAN allows the learning of deep representations in the absence of substantial labelled training information. Computer vision, language and video processing, and image synthesis are just a few of the applications that might benefit from these representations. The purpose of this research is to get the reader conversant with the GAN framework as well as to provide the background information on Generative Adversarial Networks, including the structure of both the generator and discriminator, as well as the various GAN variants along with their respective architectures. Applications of GANs are also discussed with examples. Keywords: Generative Adversarial Networks (GANs), Generator, Discriminator, Supervised and Unsupervised Learning,…

The purpose of this study is to familiarise the reader with the foundations of neural networks. Artificial Neural Networks (ANNs) are algorithm-based systems that are modelled after Biological Neural Networks (BNNs). Neural networks are an effort to use the human brain's information processing skills to address challenging real-world AI issues. The evolution of neural networks and their significance are briefly explored. ANNs and BNNs are contrasted, and their qualities, benefits, and disadvantages are discussed. The drawbacks of the perceptron model and their improvement by the sigmoid neuron and ReLU neuron are briefly discussed. In addition, we give a bird's-eye view of the different Neural Network models. We study neural networks (NNs) and highlight the different learning approaches and algorithms used in Machine Learning and Deep Learning. We also discuss different types of NNs and their applications. A brief introduction to Neuro-Fuzzy and its applications with a comprehensive review of NN technological advances is provided.

Crop yield prediction is an application that helps farmers to improve crop yield. As selection of every crop is very important in agricultural planning, it mainly depends on market price, climate and production rate. The proposed project predicts the crop yield quantity, based on the following factors Temperature, Humidity, Moisture level of soil and area of field. The rate of yield predicted by our proposed project is displayed as an output to the user that aids the farmer to harvest the crop.

Abstract: The technology round the usage of mask with the aid of using the general public to hinder COVID-19 transmission is advancing rapidly. In this narrative overview, we expand an analytical framework to study masks utilisation, synthesising the applicable literature to tell more than one areas: populace impact, transmission characteristics, supply control, wearer protection, sociological considerations, and implementation considerations. A number one direction of transmission of COVID-19 is thru breathing debris, and it's far recognised to be transmissible from presymptomatic, paucisymptomatic, and asymptomatic people. Reducing ailment unfold calls for things: proscribing contacts of inflamed people thru bodily distancing and different measures and lowering the transmission chance according to touch. The preponderance of proof shows that masks sporting reduces transmissibility according to touch with the aid of using lowering transmission of inflamed breathing debris in each laboratory and medical contexts. Public masks sporting is handiest at lowering unfold of the virus…

In this project, novel circuits for FULL ADDER are proposed using new XOR or XNOR gates. The conventional design of XOR or XNOR gates shows that the not gate in the schematic has drawbacks. So by investigating advanced XOR or XNOR gates we proposed the schematic design. The proposed schematics are optimized in terms of speed, delay, power and power delay product. We developed six novel hybrid full adder schematics based on exploring new XOR or XNOR gates. Each designed schematics have their specifications of energy consumption, delay, power delay product. To simulate the performance of the proposed designs, we use mentor graphics, tanner tool. The simulation yields a 45-nm CMOS innovation model that focuses on the proposed plans having best speed and power other than the plan of any full adder. The proposed Full Adders has 2-28% increment in consumption of energy and power delay product compared to other design schematics. The proposed hybrid full adders are investigated with voltage 1.8V, speed ,size of transistors, area, power consumption and delay.

The aim of this review paper is to present a critical analysis of existing methods of thin film deposition. Paper discusses some thin film techniques which are advanced and popular. The advantages and disadvantages of each method are mentioned. The two major areas of interest discussed are physical and chemical vapor deposition techniques. In general, thin film is a small thickness that produces by physical vapour deposition (PVD) and chemical vapour deposition (CVD). Despite the PVD technique has a few drawbacks, it remains an important method and more beneficial than CVD technique for depositing thin films materials. It is examined that some remarkable similarities and difference between the specific methods. The sub methods which are having common principle are classified. The number of researchers attempted to explain the how the specific method is important and applicable for the deposition of thin films. In conclusion the most important method of depositing thin films is CVD. For our research work the Spray Pyrolysis technique, which is versatile and found suitable to use.

End-user equipment fails or malfunctions because to power quality issues. Outages and service interruptions affect utility distribution networks, sensitive industrial loads, and important commercial operations, resulting in considerable financial losses for everybody involved. With the restructuring of power networks and the transition towards distributed and scattered generation, the issue of power quality will take on new dimensions. Take positive efforts in this area in developing countries like India, where the volatility in power frequency and many other variables of power quality are serious concerns. As a result of this study, measures that can improve the quality of power are advised. Three-stage control transmission framework with wide compensation range was proposed for Hybrid Static Synchronous Compensator (half and half D-STATCOM) by this technology. Due to these distinct properties, the cost of the framework can be drastically reduced. The circuit design of mixed D-STATCOM is provided first in this proposal. Its V–I trademark is then dissected, studied, and compared to…

This report highlights the role of AI in digital marketing to change consumer behaviour. It relates the technical aspects of modern technology with digital marketing and their use considering the changes in trends and consumer preferences based on new products and market analysis. Artificial Intelligence is a technology that makes the computers or machines as smart as human being so that they are capable of doing tasks like a human brain. As in this era of technology AI continuous to advance, it is used in almost every field of life. It is combined with digital marketing to make it easier for firms to reach the right customers at the right time. Artificial Intelligence helps the firms to get perception about the customer needs in a very short frame and effectively which boosts their sales and revenues. Some techniques that are used in digital marketing utilizing AI include Big Data analysis, machine learning and customer insights of the specific sector. India has 280 Million facebook users that makes it the top country having the biggest Facebook audience, Inida is second highest…

Fake news always has been a problem. We, too, might have fallen for a false rumor at least once in our lifetime. Moreover, the fight against fake news over social networking media is intricate. Misinformation related to home remedies for COVID 19 that have not been verified, fake news for lockdown extension or release, casualties and damage in any riots, fake consultancies, and conspiracy were prevalent during the lockdown. Many Researchers have implemented several algorithms for the detection of Fake News. In this paper, we have used several past published research papers along with our research to compare the performances of three algorithms, i.e., Naive Bayes classifier, Logistic Regression, and Support Vector Machine. This provides an idea of the most practical and efficient algorithm, Support Vector Machine, that can be used for fake news detection.

Personality assessment of candidate has been considered a most challenging task.It is helping recruiters to perform analysis of Strength, Weakness, Opportunities, Threat of the candidate.SWOT analysis is also an indicator of job satisfaction and job performance.Judging one's personality is an important part of selection process which helps recruiters to analyse the credibility of the candidate.Objective of such research is to predict the personality considering candidates answers in interview questions.This paper has presented different techniques and models used for personality assessment.Various existing research works are considered for predicting traits of person.The methodology used by existing research works are presented along with the scope of research in field of personality assessment with reference to interview answers.

Abstract: In the present scenario, it is quite aware that almost every field is moving into machine based automation right from fundamentals to master level systems. Among them, Machine Learning (ML) is one of the important tool which is most similar to Artificial Intelligence (AI) by allowing some well known data or past experience in order to improve automatically or estimate the behavior or status of the given data through various algorithms. Modeling a system or data through Machine Learning is important and advantageous as it helps in the development of later and newer versions. Today most of the information technology giants such as Facebook, Uber, Google maps made Machine learning as a critical part of their ongoing operations for the better view of users. In this paper, various available algorithms in ML is given briefly and out of all the existing different algorithms, Linear Regression algorithm is used to predict a new set of values by taking older data as reference. However, a detailed predicted model is discussed clearly by building a code with the help of Machine…

Nowadays death due to heart disease has been common in the world.It has become a hard task for the medical practitioners to diagnose in the initial stage and requires more expertise and demand in the medical field for prediction.Designing an automated system by using machine learning algorithm will improve the medical efficiency and also reduce the cost.In this paper we are planning to design an automated system that can be used for efficiently predicting the results which give information about the risks need to be faced by the patients with respect to heart diseases by using the parameter available in the dataset.We are extracting the hidden patterns from the parameters by applying data mining techniques.Since the heart data is too massive and complex for analysis using traditional techniques, we are using machine learning algorithm for computation using the parameters available in the dataset and produce accurate prediction of heart disease. Machine Learning Prediction techniques like Naive Bayes Classifier, Gaussian Naïve Bayes Classifier and Decision tree can be used to analyze…

Abstract: The Software Development Life Cycle (SDLC) refers to a methodology with clearly defined processes for creating highquality software which are cost effective and reliable. This method of software developing process is quite systematic and structural. SDLC defines the framework that has different activities and tasks to be administered during the software development process. Software development process is quite complex, and to do it without any proper planning would be inefficient. So, we use these SDLC models to make the Software development process simple and systematic. There are various software development life cycle models that are used in the software development process, all having their own advantages and limitations. In this paper, we have included six of these SDLC models - Waterfall Model, Spiral Model, V Model, Agile Model, Iterative Model and Rapid Application Development (RAD) Model. These Software Development processes have their own Advantages and Disadvantages, and the main purpose of this paper is to explain these models and know the difference between…

Abstract: Speech Emotion Recognition, abbreviated as SER, the act of trying to identify a person's feelings and relationships. Affected situations from speech. This is because the truth often reflects the basic feelings of tone and tone of voice. Emotional awareness is a fast-growing field of research in recent years. Unlike humans, machines do not have the power to comprehend and express emotions. But human communication with the computer can be improved by using automatic sensory recognition, accordingly reducing the need for human intervention. In this project, basic emotions such as peace, happiness, fear, disgust, etc. are analyzed signs of emotional expression. We use machine learning techniques such as Multilayer perceptron Classifier (MLP Classifier) which is used to separate information provided by groups to be divided equally. Coefficients of Mel-frequency cepstrum (MFCC), chroma and mel features are extracted from speech signals and used to train MLP differentiation. By accomplishing this purpose, we use python libraries such as Librosa, sklearn, pyaudio, numpy and audio…

Abstract: When humans see an image, their brain can easily tell what the image is about, but a computer cannot do it easily. Computer vision researchers worked on this a lot and they considered it impossible until now! With the advancement in Deep learning techniques, availability of huge datasets and computer power, we can build models that can generate captions for an image. Image Caption Generator is a popular research area of Deep Learning that deals with image understanding and a language description for that image. Generating well-formed sentences requires both syntactic and semantic understanding of the language. Being able to describe the content of an image using accurately formed sentences is a very challenging task, but it could also have a great impact, by helping visually impaired people better understand the content of images. The biggest challenge is most definitely being able to create a description that must capture not only the objects contained in an image, but also express how these objects relate to each other. This paper uses Flickr_8K dataset and Flickr8k_text…

In our everyday life we go over numerous individuals who are experiencing some sort of Diseases. Prediction of disease is an integral part of treatment. In this project the disease is accurately predicted by looking at the symptoms of the patient where the patient can input his/her symptom and the system will predict the disease patient is suffering from. Classification Algorithms like the Naïve Bayes (NB), Random Forest, Logistic Regression and KNN have been broadly utilized to anticipate the Disease, where different accuracies were obtained. In corresponding to a particular Disease, for example, Heart Disease, Diabetes and so on is additionally anticipated by demonstrating “True” or “False” i.e. if an individual is having or not having that Disease. Prediction of such a system can have a very large potential in the medical treatment of the future. Once the Disease is predicted by the system, It then recommends which type of doctor to consult. In this paper, an audit of some new works identified with utilization of Machine Learning in expectation of disease is predicted. An…

Cloud computing is the on-demand availability of computer system resources, especially data storage (cloud storage) and computing power, without direct active management by the user.By using Cloud storage, users can access applications, services, software whenever they require over the internet.Users can put their data remotely to cloud storage and get benefit of on-demand services and application from the resources.The cloud must have to ensure data integrity and security of data of user.The issue about cloud storage is integrity and privacy of data of user can arise.To maintain to overkill this issue here, we are giving public auditing process for cloud storage that users can make use of a third-party auditor (TPA) to check the integrity of data.Not only verification of data integrity, the proposed system also supports data dynamics.The work that has been done in this line lacks data dynamics and true public audit ability.The auditing task monitors data modifications, insertions and deletions.The proposed system is capable of supporting public audit ability, data dynamics and…

The research paper simulates airflow in a supersonic De Laval nozzle and explores air flow actions isolated from the local area's nozzle. The pressure levels in the input portion of the nozzle (pressure-inlet condition) and the atmospheric output parts (pressure-outlet condition) are used to replicate the current model. The fluid divides the motion of a lambda shock, led to a series of expansion and compression waves; for 1:4 < NPR < 2:4, the estimation shows the probability of an asymmetric flow structure. Computationally obtained asymmetric flow models are compatible with previous theoretical flow visualization studies. The nozzle pressure ratio (NPR) is equivalent to balancing the nozzle's inlet air pressure to the ambient pressure. Thus, the value of the nozzle pressure ratio in the current system is 1.5, and the amount of inlet air pressure and the pressure at the output is equal to the ambient pressure. The data contrast review indicates adequate coordination between the experimental data and the simulation outcomes. The surrounding zone is also affected during the shock wave…

Abstract: Due to rapid proliferation in the number of vehicles on the road, finding a vacant car parking space is becoming challenging and ubiquitous in every major city, resulting traffic problems are bound to exist. Increase in traffic causes the number of accidents thatcause serious bodily harm to the road users, the pollution caused by the large amount of CO2 released by the vehicles, and the continuous stress of drivers who must drive in often narrow and very busy roads and who must look for a long time to find a space to park. Thus, tosolve the parking problem, lot of research is being done on smart parking management system mechanisms. The existing system gives us the information about the empty slots availability but does not give information about the exact location of parking slot available in sucha big area. This paper proposes an efficient, cost effective smart car Parking System on wireless Sensor Networks (WSN) technology using LabView that can easily locate and secure a vacant parking space at any car park deemed convenient to them. The parking slots are continuously…

Customers will be able to reserve their vehicles from anywhere in the world due to the Car Rental System. Consumers provide information to this application by filling in their personal information. When a consumer creates an account on the website, he or she can reserve a car. The proposed system is an online system that is fully integrated. It effectively and efficiently automates manual procedures. Customers are aided by this automated method, which allows them to fill in the specifics according to their needs. It contains information on the sort of car they want to hire as well as the location. The goal of this system is to create a website where customers can book their automobiles and request services from anywhere in the world. There are three phases to this car rental system mentioned in the introduction.

Natural Language Processing (NLP) could be a branch of Artificial Intelligence (AI) that allows machines to know the human language. Its goal is to form systems that can make sense of text and automatically perform tasks like translation, spell check, or topic classification. Natural language processing (NLP) has recently gained much attention for representing and analysing human language computationally. It's spread its applications in various fields like computational linguistics, email spam detection, information extraction, summarization, medical, and question answering etc. The goal of the Natural Language Processing is to style and build software system which will analyze, understand, and generate languages that humans use naturally, so as that you just could also be ready to address your computer as if you were addressing another person. Because it’s one amongst the oldest area of research in machine learning it’s employed in major fields like artificial intelligence speech recognition and text processing. Natural language processing has brought major breakthrough within the…

Stock market is one of the most complicated and sophisticated ways to do business. Small ownerships, brokerage corporations, banking sectors, all depend on this very body to make revenue and divide risks; a very complicated model. However, this paper proposes to use machine learning algorithms to predict the future stock price for exchange by using pre-existing algorithms to help make this unpredictable format of business a little more predictable. The use of machine learning which makes predictions based on the values of current stock market indices by training on their previous values. Machine learning itself employs different models to make prediction easier and authentic. The data has to be cleansed before it can be used for predictions. This paper focuses on categorizing various methods used for predictive analytics in different domains to date, their shortcomings.

NFTs are newest entry to possibly groundbreaking technology stemming from blockchain.NFTs have caused a lot of stir in creative media market and everyday transaction consisting of NFTs are a common sight while some even making headlines.We take theoretical view of all that NFT is and all that it can possibly be.Explaining its working in its current setup, we look at its benefits and limitation.We also discuss its role in creative media market and present it as possible solutions to problems in field of event ticketing.

Abstract: Fake Products is a serious issue, as in today’s world we can’t really distinguish between real and fake product. And some people make these fake products just to make some profit without thinking about its impact on user and also affects company’s name, profit and sales. Blockchain technology can be used to detect whether the product is real or fake and assure user about the authenticity of the product. Blockchain is a trending technology and lot of applications are using this technology. Blockchain technology is the technology where information is stored in the form of blocks in many databases which is connected with the chains and it doesn’t require any third-party users for permission. Benefits of blockchain is that it is immutable and secure. It is decentralized and distributed. We can use Quick Response [1] (QR) code or an encrypted unique code which is a very efficient technique to detect fake product. When the QR code is scanned or the unique code in entered, it will redirect us to the blockchain containing the information of the product and provides us the details…

Abstract: Mathematics is a field of science that studies numbers and how they are used. It includes calculations, computations, and problem solving, among other things. It is a subject that is accurate, precise, methodical, and logical. Mathematics has been defined in a variety of ways throughout history; it is an indispensible component of science and is utilized in virtually every discipline, including natural science, engineering, art, and economics. Mathematics is a vital instrument in our lives and in every scientific field that promotes personal growth and development on a broad scale. To avoid chaos and confusion, mathematics makes life smoother and more organized. Problem solving, creativity, critical thinking, and reasoning capacity are some of the traits and talents fostered by mathematics. Other unique skills include analyzing and communicating effectively. Everyone requires mathematics in their daily lives, whether they are a cook or a farmer, a carpenter or a mechanic, a shopkeeper or a doctor, an engineer or a scientist, a musician or a magician. Therefore, it would be…

The Indian economy relies heavily on agriculture productivity. A lot is at stake when a plant is struck with a disease that causes a significant loss in production, economic losses, and a reduction in the quality and quantity of agricultural products. It is crucial to identify plant diseases in order to prevent the loss of agricultural yield and quantity. Currently, more and more attention has been paid to plant diseases detection in monitoring the large acres of crops. Monitoring the health of the plants and detecting diseases is crucial for sustainable agriculture. Plant diseases are challenging to monitor manually as it requires a great deal of work, expertise on plant diseases, and excessive processing time. Hence, this can be achieved by utilizing image processing techniques for plant disease detection. These techniques include image acquisition, image filtering, segmentation, feature extraction, and classification. Convolutional Neural Network’s(CNN) are the state of the art in image recognition and have the ability to give prompt and definitive diagnoses. We trained a deep…

In its definition, the term 'currency' defines an agreed-upon exchange item, the national currency being the legal entity used by the selected controlling entity. Throughout history, issuers have faced 1 common threat: counterfeit. In recent years fake money note has been printed that has resulted in significant losses and damage to society. Therefore, it becomes necessary to build a tool for earning money. This research project proposes a way to look at the note of counterfeit money distributed in our country through their image. After selecting an image use pre-processing. In pre-processing, the acquired image is cropped, smooth, and adjust. Change the image to grey-scale. After conversion use image separation. Features are extracted and reduce. Finally, compare the picture to be real or fake. Duplicate money has been a major problem in the market. There are currency counting machines available in banks and other trading venues to check financial authenticity. Most people do not have access to such programs which is why there is a need for fake money laundering software, which can…

Solar energy is a clean, easily accessible and abundantly available alternative energy source in nature. Getting solar energy from nature is very beneficial for power generation. Using a fixed Photovoltaic panels extract maximum energy only during 12 noon to 2 PM in Nigeria which results in less energy efficiency. Therefore, the need to improve the energy efficiency of PV solar panel through building a solar tracking system cannot be over-emphasized. Photovoltaic panels must be perpendicular with the sun in order to get maximum energy. The methodology employed in this work includes the implementation of an Arduino based solar tracking system. Light Dependent Resistors (LDRs) are used to sense the intensity of sunlight and hence the PV solar panel is adjusted accordingly to track maximum energy. The mechanism uses servo motor to control the movement of the solar panel. The microcontroller is used to control the servo motor based on signals received from the LDRs. The result of this work has clearly shown that the tracking solar panel produces more energy compared to a fixed panel.

: Heart disease has been one of the ruling causes for death for quite some time now. About 31% of all deaths every year in the world take place as a result of cardiovascular diseases [1]. A majority of the patients remain uninformed of their symptoms until quite late while others find it difficult to minimise the effects of risk factors that cause heart diseases. Machine Learning Algorithms have been quite efficacious in producing results with a high level of correctness thereby preventing the onset of heart diseases in many patients and reducing the impact in the ones that are already affected by such diseases. It has helped medical researchers and doctors all over the world in recognising patterns in the patients resulting in early detections of heart diseases.

: In recent time’s stock market predictions is gaining more attention, maybe due to the fact that if the trend of the market is successfully predicted, the investors may be better guided. A stock exchange is a system where you can buy and sell stocks. By stock we mean the share in the ownership of the company. Companies buy stocks to get the money they need to grow. Whereas people buy the stocks, also called as securities as investment or ways of possibly earning money. A stock Market Prediction model will help people to predict particular company’s stock price before they want to invest. This system will help people to invest wisely.

In any construction project there are certain hindrances which affect the duration of project and obviously on the total cost.The constraints in any project limit their achievement of high performance.The aim and scope of this study is to identify the major constraints and their level of impact on the construction projects.For this purpose a proper set of questionnaire is sent to different government bodies as well as private contractors.These questionnaires were also sent to individual involved in any project from top to bottom level.The responses from everyone is recorded and used as a major tool of this study.From the responses it was observed that there are five types of constraints viz.legal constraint, social constraints, technical constraint, environmental constraint and economic constraint.Each constraint may occur individually or they may work as a series of problems.It was observed that at every stage there may be some constraint which may affect the total duration as well as total cost of the project.The management should be adaptive and alert for any situation to…

Abstract: An Image Encryption and Decryption Using AES (Advance Encryption Standard) Algorithm is proposed in the project. Due to increasing use of image in various field, it is very important to protect the confidential image data from unauthorized access. The design uses the iterative approach with block size of 128 bit and key size of 128, 192 or 256 bit. The numbers of round for key size of 256 bits is 14 , for 128 bits is 10 and for 192 bits is 12. As secret key increases the security as well as complexity of the cryptography algorithms. In this paper , an algorithm in which the image is an input to AES Encryption to get the encrypted image and then input it to AES Decryption to get the original image is proposed and explained which will further be implemented by me. The paper shows the study in which a system could be used for effective image data encryption and key generation in diversified application areas, where sensitive and confidential data needs to be transmitted along with the image.

Abstract: The luggage tracking system is designed to track the luggage and bags which gets lost or theft from public and other areas. When people travel, there is always the chance of their luggage and bags being stolen, which is where the proposed system comes in. The luggage tracking system is based on an alert system that uses an Arduino Nano board and a GPS module. The alarm is also activated if the bag is stolen and moves outside of a certain range. Furthermore, a map is constructed via which we can monitor the location of the bag as it moves by dropping markers, which in turn informs us the location of the bag as it moves away from the owner. In this, the IOT components are being used like Arduino Board and a GPS Module in order to track the bag and to keep track of things, a frontend or mobile app is constructed. Keywords: IOT components, Arduino board, GPS, GSM model, Battery booster, Buzzer, Bluetooth model.

Movies are very significant in our lives. It is one of the many forms of entertainment that we encounter in our daily lives. It is up to the individual to decide whatever type of film they choose to see, whether it is a comedy, romantic film, action film, or adventure film. However, the issue is locating acceptable content, as there is a large amount of information created each year. As a result, finding our favourite film is really difficult. The goal of this research is to improve the regular filtering technique's performance and accuracy. A recommendation system can be implemented using a variety of approaches. Content-based filtering and collaborative filtering strategies are employed in this work. The content-based filtering approach analyses the user's history/past behaviour and recommends a list of comparable movies depending on their input. K-NN algorithms and collaborative filtering are also employed in this paper to improve the accuracy of the results. Cosine similarity is utilised in this work to quickly discover comparable information. The correctness of the cosine angle…

Thyroid Disorder is the most common condition in the medical world, caused by the thyroid gland's failure to secrete hormones.Two separate machine learning (ML) techniques, including support vector machine (SVM) and random forest, were evaluated in this paper for thyroid disorder diagnosis.The experiment was conducted on the Thyroid Dataset, which was obtained from the UCI machine learning repository.These two machine learning techniques were compared using four performance metrics: accuracy, precision, recall, and f-score.SVM is found to be better than random forest for thyroid disorder diagnosis based on the experimental findings.

Abstract: The effects of COVID-19 have tested and crushed the earlier achievement in sustaining the agricultural and extension delivery system globally. COVID-19 has pressed a reset panel on the extension services more especially among the smallholder farmers who are already underprivileged. Specifically, this review paper aims to analyse studies on the sustainability of agricultural extension delivery systems in face of the COVID-19 crisis. The various theories and factors advanced in discussing sustainable agricultural extension delivery systems, and how they contribute to improved production and productivity to end poverty have been addressed. The COVID-19 mitigation strategies and their effect on agricultural extension sustainability have been laid bare. No single sustainability theory can explain how COVID-19 has disrupted the extension delivery systems. The service providers and farmers have had their effects differently, and all players have followed mitigation to the best of their knowledge. Extension delivery has undergone numerous modifications over the years to better…

Abstract: Cyber bullying has been increasing at an unfathomable rate with the rise of the internet and the increasing radius of the social networks. This increasing amount of cyber bullying serves to be a threat to many people who are an active part of these social networks, especially the people using the social media websites for posting information and communication. These crimes have affected many people and have also resulted in suicides. Thus we need an efficient system to detect these bullying attacks and reduce their amount. In the past machine learning models have been constructed to address this problem, but those models have not been very successful. In this paper we will discuss the latest technologies like Naive Bayes, SVM, BERT models, CNN and LSTM that have been applied in this area and compare their results. Keywords: Cyber Bullying, Social Network, Machine Learning, Naive Bayes, SVM, CNN

Abstract: The central idea of Component Based Engineering is to develop a system software by selecting the well defined software components not used often and assembling them with certain system architecture. Nowadays the software development pattern is far different from the earlier approach as many new concepts are being taken into consideration E.g. QA (QualityAssurance). This term paper includes a detailed description of all the current component based software techniques used as well as their advantages and disadvantages. We also address the quality assurance issue of component based software engineering.

A large proportion of online comments available on public domains are usually constructive. However, a significant proportion is toxic and destructive. Several platforms and social media sites are finding it difficult to maintain fair conversation and are often forced to either limit the user comments or get dissolved by shutting down user comments completely. So, to prevent these types of identity hate through comments on social media, we come up with a solution to detect different types of toxicity in the comments using Deep Learning and Natural Language Processing. Dataset is obtained online which is processed to remove noise. Transformation of raw comments is done before feeding it to the classification model using Natural Language Processing. A Convolutional Neural Network model is used which will differentiate toxic comments from non-toxic comments.

The social distancing detection using deep learning is to evaluate the distance between people to mitigate the impact of this coronavirus pandemic.The detection tool was developed to alert people to maintain a safe distance with each other.The open-source object detection pre-trained model based on the YOLOv3 algorithm was employed for pedestrian detection.The distance between people can be estimated and any noncompliant pair of people in the display will be indicated with a red frame.The number of people in an image and video with bounding boxes can be detected via the YOLO method which was employed to detect the video stream taken by the camera.We will be using YOLOv3, trained on COCO dataset for object detection.In general, single-stage detectors like YOLO tend to be less accurate than two-stage detectors and are significantly faster.YOLO treats object detection as a regression problem, taking a given input image and simultaneously learning bounding box coordinates and corresponding class label probabilities.

Abstract: A Brain tumor is one aggressive disease. An estimated more than 84,000 people will receive a primary brain tumor diagnosis in 2021 and an estimated 18,600 people will die from a malignant brain tumor (brain cancer) in 2021.[8] The best technique to detect brain tumors is by using Magnetic Resonance Imaging (MRI). More than any other cancer, brain tumors can have lasting and life-altering physical, cognitive, and psychological impacts on a patient’s life and hence faster diagnosis and best treatment plan should be devised to improve the life expectancy and well-being of these patients. Neural networks have shown colossal accuracy in image classification and segmentation problems. In this paper, we propose comparative studies of various deep learning models based on different types of Neural Networks(ANN, CNN, TL) to firstly identify brain tumors and then classify them into Benign Tumor, Malignant Tumor or Pituitary Tumor. The data set used holds 3190 images on T1-weighted contrast-enhanced images which were cleaned and augmented. The best ANN model concluded with an…

Heart diseases have been the primary reason for death all over the world. Majority of the deaths related to cardiovascular problems are caused by heart attacks and strokes. The World Health Organization (WHO) indicates that an approximate 17.9 million people die due to such diseases every year. Therefore, it is essential that we find methods to ensure the minimization of these numbers. In order to minimize the detrimental effects of heart diseases, we must try to predict its presence at earlier stages. Machine Learning algorithms can help us effectively predict such results with a high degree of accuracy which can in turn help doctors and patients detect the onset of such diseases and reduce their impact or prevent them from occurring. Our objective is to create a system that is able to accurately determine the presence of heart disease in a time and cost efficient manner.

This paper briefly examines the interpretation of RestFul APIs, its methods, and responses. It explains how REST (Representational State Transfer) is preferred over SOAP (Simple Object Access Protocol). Majority of the IOT devices are not straightaway related to each other. They are connected via services that provide interfaces to users. In this paper, the author addresses how the Internet of Things (IoT) can get profited from APIs. This paper also introduces a guide for Application Programming Interface (API) documentation.

Abstract: This paper examines the overview of low-code/no-code development platforms in comparison with traditional development methodologies and examines the benefits and limitations of the same. For several decades, businesses have had multiple options when they demanded new information systems. They could develop a new system using in-house developers, or they could order a system from an external merchant. This offers a close fit to business obligations. However, nowadays, there is a new alternative that is becoming increasingly prevalent. Low code/no code (LC/NC) applications can cater to business requirements efficiently, can be implemented instantly, and the cost is much less than systems developed in-house. Few, if any, programming skills are required. Keywords: Traditional development, No code development, low code development, Low code No code development, Software development life cycle (SDLC)

Abstract: Cloud services are being provided by various giant corporations notably Amazon Web Services, Microsoft Azure, Google Cloud Platform, and others. In this scenario, we address the most prominent web service provider, which is Amazon Web Services, which comprises the Elastic Compute Cloud functionality. Amazon offers a comprehensive package of computing solutions to let businesses establish dedicated virtual clouds while maintaining complete configuration control over their working environment. An organization needs to interact with several other technologies; however, instead of installing the technologies, the company may just buy the technology available online as a service. Amazon's Elastic Compute Cloud Web service, delivers highly customizable computing capacity throughout the cloud, allowing developers to establish applications with high scalability. Explicitly put, an Elastic Compute Cloud is a virtual platform that replicates a physical server on which you may host your applications. Instead of acquiring your own hardware and connecting it to a network, Amazon…

In both created and non-industrial nations, proceeded with openness to helpless air quality is a significant general wellbeing hazard. Poisons that add to helpless air quality are thought to cause over 2.5 million unexpected losses every year all throughout the planet. To monitor things, In this undertaking, we will make an IOT-based Air Pollution Monitoring System in which we will display the quality of air in the mobile application utilizing a GSM and will set off a caution when the air quality drops under a particular range, for example when there is an enough measure of gases which are hurtful like CO2, smoke, liquor, benzene, and NH3 present noticeable all around. It will show the air quality in the proportion of PPM on the LCD and on the versatile application with the goal that we can without much of a stretch screen it. We can use our mobile app to display the contamination level in this IoT project.

The point of this undertaking is to configuration, carry out and assess a picture handling programming based answer for programmed recognition and grouping of plant leaf infection. Anyway contemplates show that depending on unadulterated unaided eye perception of specialists to recognize and group infections can be tedious and costly, particularly in country regions and agricultural nations. So we present quick, programmed, modest and precise picture preparing based arrangement. Arrangement is made out of four primary stages; in the main stage we make a shading change structure for the RGB leaf picture and afterward, we apply shading space change for the shading change structure. Then, in the subsequent stage, the pictures are sectioned utilizing the K-implies bunching strategy. In the third stage, we figure the surface components for the portioned contaminated items. At long last, in the fourth stage the separated provisions are gone through a pre-prepared neural organization.

As per the definition given by the World Health Population, health alludes to the condition of complete physical, mental and social prosperity and not just the nonappearance of sickness or infirmity. It acts as a crucial parameter in the country's development. It could disrupt due to various strains resulting in Stress-the body's response to anything or a situation that requires any attention or action.Architecture is deeply contextual and responds to its social and environmental context as much as its historical and physical one.If we are designing for the ripple effect consciously, we benefit the individuals and support the community.By creating a healing space, one evokes the feelings of serenity, calm, and relaxation and can contribute to an environment that facilitates the natural healing process-a process of repair, recovery, and return to wholeness in mind, body, and spirit.Since there have been strong human responses to nature because these responses appear in study after study and are consistent across social, economic, cultural, and racial boundaries, buildings are the…

Abstract: Most important part of information gathering is to focus on how people think. There are so many opinion resources such as online review sites and personal blogs are available. In this paper we focused on the Twitter. Twitter allow user to express his opinion on variety of entities. We performed sentiment analysis on tweets using Text Mining methods such as Lexicon and Machine Learning Approach. We performed Sentiment Analysis in two steps, first by searching the polarity words from the pool of words that are already predefined in lexicon dictionary and in Second step training the machine learning algorithm using polarities given in the first step. Keywords: Sentiment analysis, Social Media, Twitter, Lexicon Dictionary, Machine Learning Classifiers, SVM.

Abstract: The administration is becoming increasingly concerned about the spike in corona virus cases. Since the WHO declared the corona virus a pandemic, every industry has had issues. Restaurants had to shut down since only crucial facilities were allowed to operate during the lockout. The analysis' goal is to look into consumer demand for the restaurant industry. An online survey with questionnaires was used to collect data. Using the Henry Garret technique and the Percentage method, this study looked at how customers' tastes have changed. Restaurant tastes are drastically different before and after Covid-19. This study definitely answers the questions around Covid19's impact on restaurants.

Abstract: Heart diseases are the one of the primary reasons of human death today. There are many recent technologies are used to assist the medical professionals and doctors in the prediction of heart disease in the early stage. Prediction of heart disease is a critical challenge in the area of clinical data analysis. This paper introduces a technique to detect arrhythmia, which is a representative type of cardio vascular diseases. Arrhythmia refers to any irregular change from the normal heart rhythms, means that your heart beats too quickly, too slowly, or with an irregular pattern. The Electro Cardiogram (ECG) is used as an input for the arrhythmia detection. It displays the rhythm and status of the heart. This paper propose an effective ECG arrhythmia classification approach based on a deep convolutional neural network (CNN), which has lately demonstrated remarkable performance in the field of machine learning. It perform the classification without any manual pre-processing of the ECG signals such as noise filtering, feature extraction, and feature reduction. Keywords:…

Abstract: This is the era of modern technology where we are all surrounded and covered by technology. This eases our daily life and saves our time and one of the most important techniques that played a very important role in our day-to-day life is the recommendation system. The recommendation system is used in various fields like it is used to recommend products, books, videos, movies, news, and many more. In this paper, we use a Recommendation system for movies we built or a movie recommendation system. It is based on a collaborative filtering approach that makes use of the information provided by the users, analyzes them and recommends movies according to the taste of users. The recommended movie list sorted according to the ratings given to this system is developed in python by using pycharm IDE and MYSQL for database connectivity. The presented recommendation system generates recommendations using various types of knowledge and data about users. Our Recommendation system recommends movies to each and every user by their previous searching history. Here we use some searching…

Abstract: In this paper, mainly three machine learning algorithms are discussed in detail and how they work is shown, their pseudo codes are shown and a comparison is done among them, and their performance is analyzed. Keywords: Machine Learning, pseudo code, algorithms, data

Abstract: Mesgaran copper deposit is located in Sarbisheh city of South Khorasan province of Iran. To investigate the geochemical changes of the elements with increasing depth in the deposit, geochemical sections for important minerals related to mineralization in the area including copper, lead, zinc and cobalt were drawn for 9 exploratory boreholes. In these sections, the trend of changes of different elements versus depth is shown and the resulting diagrams were drawn for different boreholes. As a result, there is a significant relationship between the elements. With increasing the drilling depth, the amount of copper decreased and the amount of copper in each section was determined according to its cause. Keywords: Geochemistry, Copper deposit, Exploratory borehole, geochemical section.

Abstract: Cyber security acknowledges an enthusiastic job in the space of data innovation. Shielding the data has become a gigantic issue in the current day. The cyber security the primary concern that begins as a top priority is 'digital violations' which are increasing on large scale. Today, network protection is at a critical concern to many. At whatever point we contemplate the network protection the primary thing that rings a bell is 'digital wrongdoings' which are expanding colossally step by step. This paper generally points out on the network protection, cybersecurity and digital psychological warfare. The digital psychological oppression could cause relationship to lose billions of dollars in the area of associations. Keywords: Network, Cyber Security, Digital, Data Security

A person while driving a vehicle - if does not have proper sleep or rest, is more inclined to fall asleep which may cause a traffic accident. This is why a system is required which will detect the drowsiness of the driver. Recently, in research and development, machine learning methods have been used to predict a driver's conditions. Those conditions can be used as information that will improve road safety. A driver's condition can be estimated by basic characteristics age, gender and driving experience. Also, driver's driving behaviours, facial expressions, bio-signals can prove helpful in the estimation. Machine Learning has brought progression in video processing which enables images to be analysed with accuracy. In this paper, we proposed a method for detecting drowsiness by using convolution neural network model over position of eyes and extracting detailed features of the mouth using OpenCV and Dlib to count the yawning.

There is no reason that a critical educational practise like attendance should be viewed in the old, tedious manner in this age of rapidly evolving new technologies. In the conventional method, it is difficult to manage large groups of students in a classroom. Since it takes time and has a high risk of error when entering data into a system, it is not recommended. Real-Time Face Recognition is a practical method for dealing with a large number of students' attendance on a daily basis. Many algorithms and techniques have been developed to improve face recognition performance, but our proposed model employs the Haarcascade classifier to determine the to determine the positive and negative characteristics of the face, as well as the LBPH (Local binary pattern histogram) algorithm for face recognition, all of which are implemented in Python and the OpenCV library. For user interface purposes, we use the tkinter GUI interface.

In the field of Husbandry, its little difficult to detect the breed of animals in order to estimate the commercial value production.Usually it can be classified with the help of DNA testing but its expensive and sometime not affordable.Lameness in sheep is one of the concerns which is to be taken care.It usually happens due to inadequate of healthcare and welfare among the country serving sheep industry.This paper aims to classify the sheep according to their respective breed.Basically 4 breeds have been taken into consideration and by applying neural networks, the sheep breed has been classified.Throughout the task the accuracy of 99.97% was achieved while training the CNN model & 87.1% was achieved while testing the model.With the help of this classifier, sheep farmer can identify the breed more accurately and efficiently.

Artificial Intelligence (A.I.) is the quickest developing field of software engineering and innovation. It has accomplished an extraordinary achievement in limited ability to focus time. It is essentially the cycle of reflecting human insight to machines. In this paper, we have detailed the idea and the models of Man-made brainpower alongside its future degree.

Plants have developed an imperative source of energy and aimportant problem in solving the problem of global warming. However, plant diseases threaten the livelihoods of this important source. Convolutional Neural Networks (CNN) have shown excellent performance (more than humans) in recognizing problems and image classification problems. This paper describes the possibility of classifying plant diseases with leaf images taken by CNN in the natural situation. The model is designed based on the Le-Net architecture for organization of soybean plant diseases, including healthy leaf images taken from the plant village database. Performance evaluations on several popular benchmark datasets prove that our method is better than the latest technology. This article proposes a method to improve the classification performance of classes with few training examples

Abstract: Users can use book recommendation systems to search and select books from a number of options available on the web or elsewhere electronic sources. They give the user a little bit selection of products that fit the description, given a large group of objects and a description of the user needs. Our system will simply provide recommendations. Recommendations are based on previous user activity, such as purchase, habits, reviews, and likes. These systems gain lot of interest. In the proposed system, we have a big problem: when the user buys book, we want to recommend some books that the user can enjoy. Buyers also have a great deal of options when it comes to recommending the best and most appropriate books for them. User development privacy while placing small and minor losses of accuracy. Recommendations. The proposed recommendation system will provide user's ability to view and search the publications and using the Support Vector Machine (SVM), will list the most purchased and top rated books based on the subject name given as input. Keywords: Recommender System, Support…

Abstract: Man has needed and used energy at an increasing rate for the sustenance and well-being since time immemorial. Due to this a lot of energy resources have been exhausted and wasted. Proposal for the utilization of waste energy of foot power with human locomotion is very much relevant and important for highly populated countries like India where the railway station, temples etc., are overcrowded all round the clock. When the flooring is engineered with piezo electric technology, the electrical energy produced by the pressure is captured by floor sensors and converted to an electrical charge by piezo transducers, then stored and used as a power source. And this power source has many applications as in agriculture, home application and street lighting and as energy source for sensors in remote locations. This paper is all about generating electricity when people walk on the Floor. Think about the forces you exert which is wasted when a person walks. The idea is to convert the weight energy to electrical energy The Power generating floor intends to trans- late the kinetic energy…

A. GeneralConcrete is a construction material basically mixture of coarse aggregate, fine aggregate and cement.Concrete plays a vital role in many structures such as buildings, bridges, canals etc. Concrete becoming a interior part of any type of construction works, the usage of concrete is becoming more due to development of construction industry.The performance of concrete is depend upon the properties of aggregates in order to reduce the consumption of concrete components.Usage of pozzolana such as flyash, rice husk ash, bagasse ash by replacing cement at a certain amount to produce good concrete.The usage of concrete is twice as compared to aluminium, plastic, wood etc. Concrete is a versatile material used in all type of structural works.Portland pozzolana cement is recognized as a major construction material throughout the world.Researchers all over the world today are focusing on ways of utilizing either industrial or agricultural waste, as a source of raw materials for industry.This waste, utilization would not only be economical, but may also result in foreign exchange…

Abstract: In the earlier days, students had to visit the college to enquire about details like courses, fee structure, admission process and other information's about the college, which is a tiresome and long process . This is where we thought of using an intelligent bot delivering the information. College Enquiry Chatbot is a simple python web application which aims to provide the information regarding college asked by the user. Keywords: Chatbot, Python, ChatterBot, Django

Abstract: Rapid industrialization and sudden growth of population around the globe from the 18th century onwards ultimately led to the uncontrolled growth of manufacturing and energy producing industries. To make processes economical industries side lined the environment which began showing its effects from the past 50 years. Ever since Global Warming (commonly attributed to the unhealthy quantities of greenhouse gasses) starting to take up the centre stage, environmentalist and chemical engineers around the globe felt the need to reinvent our industrial processes to balance economy with environmental health. Through the medium of this report we intend to highlight yet another essential need of the hour that not only has the potential to reverse the damage of high carbon release by industries but also maintain economics of plant operation. Although Carbon capture is already a subject that is in study by scientists and engineers around the globe we intend to contribute and understand its plausibility using technology and simulation as a tool to facilitate better understanding of Co2…

Electrically conductive adhesives (ICAs; Isotropic Conductive Adhesive, ACAs; An-isotropic Conductive Adhesive &NCAs; Non-conductive Adhesive) offer interconnection of materials which can be used in electronic packaging to replace the traditional solders due to its advantagessuch as eco-friendliness, simple applying process, low curing temperature, and costeffectiveness.ICAs have been developed and widely used in replacing traditional soldering, especially in die attach, surface mounting technologies and flip chip assemblies.ACAs can utilise in emerging electronic technologies like, multilayer printed circuits, thin-film transistors, smart card application etc.An electrically conductive adhesive (ECA) consist of an adhesive matrix in which the filler materials are embedded.Adhesive matrix offers towards binding properties of the ECA, where the filler materials contribute towards electrical, mechanical and thermal properties of ECAs.Apart from variety of conductive fillers incorporated into the matrix, orientation and distribution of fillers within the adhesive matrix also plays a…

Abstract: Online Identity Theft is known to be quite possibly the most genuine and developing dangers to people and organizations for the past decade because of the colossal financial harm caused by it. It is a critical form of cybercrime which uses information such a victim’s name, bank details, email address, passwords, passport or identification details, and other valuable information to gain access to accounts. This aim of this research is to make use of Machine Learning algorithms for the detection of such crimes. Keywords: identity theft; cybercrime; Machine Learning; detection; algorithms

Abstract: Due to the enormous expansion in the accessibility of music data, music genre classification has taken on new significance in recent years. In order to have better access to them, we need to correctly index them. Automatic music genre classification is essential when working with a large collection of music. For the majority of contemporary music genre classification methodologies, researchers have favoured machine learning techniques. In this study, we employed two datasets with different genres. A Deep Learning approach is utilised to train and classify the system. A convolution neural network is used for training and classification. In speech analysis, the most crucial task is to perform speech analysis is feature extraction. The Mel Frequency Cepstral Coefficient (MFCC) is utilised as the main audio feature extraction technique. By extracting the feature vector, the suggested method classifies music into several genres. Our findings suggest that our system has an 80% accuracy level, which will substantially improve on further training and facilitate music genre…

Home Automation industry is growing rapidly, this is fulfilled by the need to provide supporting systems for the elderly and the disabled, especially those who live alone. Coupled with this, the world population is confirmed to be getting older. Home automation systems must comply with the household standards and convenience of usage.Home automation is one of the major growing industries that can change the way people live. Some of these home automation systems target those seeking luxury and sophisticated home automation platforms; others target those with special needs like the elderly and the disabled. Typical wireless home automation system allows one to control household appliances from a centralized control unit which is wireless. These appliances usually have to be specially designed to be compatible with each other and with the control unit for most commercially available home automation systems.The developed system can be integrated as a single portable unit and allows one to wirelessly control lights, fans, air conditioners, television sets, security cameras, electronic…

Agriculture is one of the significant occupation in various countries including India. As major part of the Indian financial system is reliant on agriculture production, the intense consideration to the concern of food production is essential. The nomenclature and recognition of crop infection got much significance in technical as well as economic in the Agricultural Industry. While keeping track of diseases in plants with the support of experts can be very expensive in agriculture region. There is a necessity for a method or system which can automatically identify the diseases as it can bring revolution in monitoring enormous fields of crop and then plant leaflet can be taken ca The detection of cotton leaf disease is a very important factor to prevent serious outbreak.re imme4diately after recognition of disease. The aim of this paper is to provide guidelines for the development of application which recognizes cotton plant leaf diseases. For availing this user need to upload the image of the cotton leaf and then with the help of image processing one can get a digitized colour…

Abstract: This paper describes a computer-based tool for the selection of 3D printer for educational propose by using Multi Attribute Decision Making (MADM) strategies particularly Analytic Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). In education, 3D printing technologies facilitate improved learning, skills development, and increased student and teacher engagement with the subject matter. Furthermore, 3D printing sparks greater creativity and collaboration in solving problems, to settle on a best option for teaching learning process tasks into account. MADM methods are interpretative processes which are well suited in choice of different 3D printers. This work suggests AHP and TOPSIS to judge 3D printer alternatives for choice of method, based on the AHP and TOPSIS methodology, ranks available techniques by a score resulting from the composition of priorities at different levels, each considering homogeneous and independent evaluation criteria. In this work proposes a comprehensive list of key factors that have a significant…

Abstract: Now a days, automobiles became most convenient mode of transportation for everyone. As we know one of the most important functions, TSDR has become a popular research . It primarily involves the use of vehicle cameras to collect real- time road pictures and then recognize and identify traffic signs seen on the road, therefore delivering correct data to the driving system. With the advancement of science and technology, an increasing number of scholars are turning to deep learning technology to save time in traditional processes. From the training samples, this model can learn the deep features inside the autonomously. The accuracy and great efficiency of detection and identification are the subject of this essay. A deep convolution neural network algorithm is proposed to train traffic sign training sets using Caffe[3], an open-source framework, in order to obtain a model that can classify traffic signs and learn and identify the most critical of these traffic sign features, in order to achieve the goal of identifying traffic signs in the real world. Keywords: Traffic sign,…

Index Terms: Regression model, House price prediction, machine learning, housing market, Arima model, artificial neural network, support vector machine, random forest, dataset.

Abstract: Cyber security are techniques generally set forth in published materials that attempt to safeguard the cyber environment of a user or organization. It manages the set of techniques used to save the integrity of networks, programs and data from unauthorized access. It refers to the body of technologies, processes, and it may also be referred to as information technology security. The field is of growing importance due to increasing reliance on computer systems, including smart phones, televisions and the various tiny devices that constitute the Internet of Things. Keywords: IT security, Internet of things (IOT)

As the current problem of environment and noise pollution, we made a small effort to solve this problem. A solar based grass cutter is used to cut the Grass basically in lawn or garden. In this research the proper sizing of solar panel, charge Controller, battery, DC motor were calculated. The maintenance cost has been reduced by using this machine. Proper design of solar panel, battery, charge controller was by catia modelling. Cutting of grass is more time consuming and labour cost. The highly strength blades are used for cutting grass which is powered by DC motor. The present research gives the solution for quick process of cutting grass in order to make environment beautiful.

Health monitoring is the fundamental issue in this day and age. Because of absence of amazing health monitoring, patient go through from genuine medical problems. There are great deals of IoT gadgets now days to uncover the health of impacted individual over web. Wellbeing specialists are moreover exploiting these splendid contraptions to look out for their patients. With heaps of new medical care innovation new companies, IoT is suddenly changing the medical services industries. Actually in this undertaking, we will make an IoT based patient checking System which reports the patient coronary heart beat rate and assemble temperature and besides transport an email/SMS alert each time these readings go past basic characteristics. Heartbeat charge and inward warmth level readings are recorded over ThingSpeak and Google sheets so that affected individual health can be seen from wherever in the world over through on the web. A furor will in like manner be related so that affected individual can crush it on emergency to send email/SMS to their relatives.

Working in the earth presents many different security and health dangers.Frequently the underground environment is unpleasant.The mines that are deeper, the more dangerous it could be to be running jobs.This paper proposes a Mining Tracking as well as Safety system for the mining industry using microcontroller-based circuit on the worker helmet.We use RF based circuitry to detect workers moving through the entire mining site.The helmet is integrated with a RF based tracking system which in coordination with the tracker RF systems help provide data over IOT.The system makes use of Atmega microcontroller based RF tracker circuitry to receive the data transmitted by worker helmet nodes.This helps map the current location of workers through the entire mining site.Moreover, each worker helmet circuit is integrated with a panic/emergency button.This button when pressed shows an emergency sign over the IOT web interface about the worker emergency

Unmanned aerial vehicles (UAVs) are increasingly popular for civil applications due to their flight capabilities and mobility.This paper proposed an indoor patrol and surveillance system using unmanned aerial vehicles.The components were integrated successfully and the designed system was experimented in an indoor setup.Results has shown that the proposed system is suitable and feasible to be used as an autonomous patrol and surveillance agent for indoors use.An application is developed as proof of concept with detailed design that can take advantage of unmanned urban vehicle to be directly configured and controlled in real time.The advantages are numerous; it can be used for many purposes.For example, it can be used for observing critical and important area for intruder activities or to know the current state of any object of interest.Intrusion of terrorists and trespassers are adversely affecting the peace and harmony in the nation.The fatalities and disturbances caused by the latest Uri attack in Indian Army Camp show the necessity of an efficient border surveillance and intruder…

Abstract: An IoT based health monitoring system records the patient’s heart beat, body temperature, oxygen levels of blood etc. It can also be used to inform the timing of medication and provides live monitoring of health condition of patient to the doctor available in his chamber. It also sends an SMS alert whenever the health parameter readings go beyond critical values. Keywords: Heart beat, Temperature, Oxygen Levels, Medication timing, SMS alert.

Abstract: Fake news distribution is a social phenomenon that can't be avoided on a personal level or through web-based social media like Facebook and Twitter. We're interested in counterfeit news because it's one of many sorts of double dealing in online media, but it's a more severe one because it's designed to deceive people. We're concerned about this now that we've seen what's going on. We are concerned about this issue because we have seen how, through the usage of social correspondence, this marvel has recently caused a shift in the direction of society and people groupings, as well as their opinions. Along these lines, we chose to confront and decrease this wonder, which is as yet the principal factor to pick a large portion of our choices. Our objective in this study is to develop a detector that can predict if a piece of news is false based just on its content, and then attack the problem using RNN method models LSTMs and Bi-LSTMs to tackle the problem from a basic deep learning viewpoint. Keywords: RNN (Recurrent Neural Networks), LSTM (Long Short-Term Memory), Fake news…

Abstract: Early detection of disease has emerged as a critical issue in recent years due to the fast population increase seen in medical research. The chance of dying from breast cancer increases dramatically as the world’s population continues to increase at an alarming rate. Compared to other cancers discovered thus far, breast cancer is the second most severe. In addition to assisting medical staff in disease diagnosis, an automated disease detection system also provides reliable, effective, and fast intervention, which reduces the likelihood of mortality. In this research study, the Artificial Neural Network is employed for breast cancer classification. The model is validated on well-known dataset comprised from UCI machine learning repository. The results reveal that the ANNs obtained the highest accuracy i.e. 98.24%. Keywords: Machine Learning, Neural Network, Algorithm, Artificial Intelligence.

Abstract: A hydrological model helps in understanding of the hydrological processes and useful to measure water resources for effective water resources management. Hydrological cycle describes evaporation, condensation, precipitation and collection of earth water and on again. Hydrological models have been used in different watersheds across the world. The runoff estimation process is the most complex in nature that depends on the meteorological data and also on the various watershed physical parameters. To generate runoff data for a particular watershed it is needed to find out various parameters related to precipitation models. The HEC HMS (a Centre for Hydrological Engineering and Hydrological Modelling Systems introduced by the US Army Corps of Engineers) is a popularly used watershed model to simulate rainfall runoff process. The input variables used by hydrological models are rainfall data, runoff data, wind speed, relative humidity, soil type, catchment properties, hydrogeology and other properties. The Hydrological Modeling can also be an event based or may be continuous.…

Abstract: In this research an opinion of the citizens from India is carried out to get to know what do they really think of an electric vehicle over a conventional I.C. engine vehicle. To get an answer for that a survey questions is generated considering various parameters like maintenance, overall driving cost (fuel/charging), convenience to drive, pollution (noise/air), social trend, purchase intention, safety to the driver and passenger, boot carrying capacity, weight comparison, performance and mileage/range of the vehicle. The following mention parameters is converted into questions in a Google form to with 5 options from 1-5 in which 1 being strongly disagree and 5 being strongly agree for the asked questions. About 100 responses is considered for this survey from the people of various age, gender and location. In this study opinions of the people were collected to get a clear view of an electric vehicle as it is a new technology in automotive sector and what’s their mentality when it comes to comparison of electric vehicles to a conventional I.C. engine as I.C. engine has…

Abstract: Corona virus disease 2019 (COVID 19) is defined as illness caused by novel corona virus now called severe acute respiratory syndrome corona virus 2 (SARS-Cov-2; formally called as 2019-nCov), which was first identified in Wuhan City, Hubei Province, China. The spreading of COVID 19 is very fast throughout the world. World economy as well as public health has been facing a devastating effect caused by COVID 19. Hence detecting COVID 19 is challenging task even we have multiple methods like RT-PCR, COVID kits. The RT-PCR may not available in all laboratory, even exists which take some time to process and get reports and COVID 19 test kits may not available in all places. So, the main intention of this paper is to detect COVID 19 with in low budget, less time and accurate results. We have trained deep transferred learning models like ResNet-50, ResNet-101 using COVID positive, Normal, Viral Pneumonia chest x-rays. ResNet-50, ResNet-101 is pre-trained deep learning neural network. ResNet-50 provides 98% of accuracy where ResNet-101 gives us 97% of accuracy. Keywords: COVID 19,…

This course handles about the hypothesis and practices of HRM and its effect on worker execution the board in associations.Associations think that it's reasonable to adjust the two factors and perceive what they mean for one another to accomplish their proposed objectives.It is through HRM that people are given headings inside associations to perform in like manner.The following is what HRM means for worker execution the board.The terms 'human asset the board' (HRM) and's 'HR) have generally supplanted the term 'faculty the executives' as a portrayal of the cycles associated with overseeing individuals in associations.The idea of HRM supports every one of the exercises depicted in this report, and the point of this investigation is to give a structure to what follows by characterizing the ideas of HRM and a HR framework, portraying a few models of HRM and seeing its points and attributes.This further proceeds with a survey of qualms about HRM and the connection among HRM and execution the board and finishes up with a conversation of the effect HRM and execution the executives.…

Pneumonia is one of the most serious diseases which cause the most deaths in the world. Viruses, bacteria, and fungi can cause pneumonia. The infection from spreading to the lungs in the human body. In order to diagnose this infection, a chest x-ray is carried out. The doctor uses X-ray image in order to diagnose or monitor the treatment of states in which inflammation of the lungs. X-rays are also used in the diagnosis of diseases such as emphysema, lung cancer, cancer of the line, and pipe, and tuberculosis (tb). However, a diagnosis of pneumonia requiring medical experts to comment on its presence felt in the chest x-ray. For decades, the auto- diagnosis (CAD) systems have been used for the respiratory disease based on chest X-ray images. Deep learning allows machines can quickly extract and classify objects from a photo. Ilham, with the great success of deep learning, we use a deep learning approach to detection of pneumonia into the work. Convolutional neural network that was developed for this study is the inflammation of the lungs. Supervised learning is ANCHORED to the use…

Sentiment analysis is defined as the process of mining of data, view, review or sentence to Predict the emotion of the sentence through natural language processing (NLP) or Machine Learning Techniques. The sentiment analysis involve classification of text into three phase “Positive”, “Negative” or “Neutral”. The process of finding user Opinion about the topic or Product or problem is called as opinion mining. Analyzing the emotions from the extracted Opinions are defined as Sentiment Analysis. The goal of opinion mining and Sentiment Analysis is to make computer able to recognize and express emotion. Using social media, E-commerce website, movies reviews such as Face book, twitter, Amazon, Flipkart etc. user share their views, feelings in a convenient way. Sentiment analysis in a machine learning approach in which machines classify and analyze the human’s sentiments, emotions, opinions etc. about the products. Out of the various classification models, Naïve Bayes, Support Vector Machine (SVM) and Decision Tree are used maximum times for the product analysis. The proposed approach…

Technology is being used and improved by human beings over a long period of time now and Smartphones is one of them. Smart Phones contain touch screen, built in keyboard, high resolution camera, front side camera for video conferencing, etc. They are used for making and receiving calls, sending and receiving messages, accessing the Internet, digital media, incorporating audio/video recording etc. Different smart phones have different operating systems and mobile applications are developed for each operating system in smart phones, tablet or mobile phones, in order to serve the needs of the user. These apps are either preinstalled or downloadable from online app market that can do almost everything. Apps make a mobile be like a portable computer having multi core processors, gigabytes of memory and a real operating system. Originally mobile apps were made available for only calling, messaging and informational purposes like calendar, weather forecast, e- mail, etc. With improvement in technology and increase in user demands, developers started making apps for other purposes like…

Activity recognition in humans is one of the active challenges that find its application in numerous fields such as, medical health care, military, manufacturing, assistive techniques and gaming. Due to the advancements in technologies the usage of smartphones in human lives has become inevitable. The sensors in the smartphones help us to measure the essential vital parameters. These measured parameters enable us to monitor the activities of humans, which we call as human activity recognition. We have applied machine learning techniques on a publicly available dataset. K-Nearest Neighbors and Random Forest classification algorithms are applied. In this paper, we have designed and implemented an automatic human activity recognition system that independently recognizes the actions of the humans. This system is able to recognize the activities such as Laying, Sitting, Standing, Walking, Walking downstairs and Walking upstairs. The results obtained show that, the KNN and Random Forest Algorithms gives 90.22% and 92.70% respectively of overall accuracy in detecting the activities.

Human face is one of the natural traits and crucial part of human body that can uniquely identify an individual. In the current old system the roll numbers are called out by the teachers and their presence or absence is marked accordingly which is time consuming and has a lot of ambiguity that caused inaccuracy and inefficiency of attendance marking. The productive time of the class can be utilized very efficiently by implementing automated attendance system. The main purpose of this project is to build a face recognition-based attendance monitoring system for any educational institution or organization where attendance marking is the demanding task. It enhances and upgrades the current attendance system into more efficient and effective as compared to before. This attendance system which uses HaarCascade a machine learning Object Detection Algorithm used to identify faces in an image or a real time video, Local Binary Pattern Histogram (LBPH) a face recognizer algorithm used to extract features and compare by using python programming and OpenCV libraries saves time and efficiently…

Stroke is a drawn out inability sickness caused everywhere on the world and it is the third driving reason for demise. Early forecast of stroke gives more important to the current time. Stroke happens fundamentally due to individuals' way of life in the advanced time changing elements, for example, high glucose, coronary illness, weight, diabetes. In this examination, we analyze the Support vector machine, Decision tree, Random forest and XG Boost.we have utilized four AI calculations to recognize the sort of stroke that can happen or happened to structure an individual's actual state and clinical report information. We have gathered a decent number of sections from the clinics and use them to take care of our concern. The characterization result shows that the outcome is good and can be utilized continuously clinical report. We accept that AI calculations can help better comprehension of illnesses and can be a decent medical care buddy.

Agribusiness is the foundation of India. In India 50 % of the remaining task at hand depends upon agribusiness. Commitment of agriculture part in Indian economy is higher than some other division in India. In any case, Farmers utilized customary strategy for developing harvests which comes to less profitability of yields. Additionally, a soil erosion and disintegration is likewise a principle motivation to less profitability of yields. This will impact in diminishes fruitfulness level. Loss of soil supplements through different courses is likewise motivation to diminish soil richness level. The supplements like potassium (K), nitrogen (N) and phosphorus (P) are basic for the development of a plant. The advancement in agriculture is important to tackle these issues in agribusiness part and shrewd cultivating is the appropriate response. This can be conceivable utilizing IoT gadgets. Farmers can get the necessary data just as the screen is yield. IoT associates the entire world with the assistance of sensors and other installed gadgets. The diverse soil tests will be taken from…

The Currency Recognition System was developed for the purpose of fraud detection in paper currency, so this system is u sed worldwide.The uses of this framework can be recognized in banking frameworks, cash observing gadgets, cash trade frameworks.This paper proposes an automatic paper currency recognition system through an application developed using Machine learning Algorithms.The algorithm implemented is simple, robust and efficient.

The project focuses on a solution to monitor the air and noise pollution levels in industrial environment or by using wireless embedded computing system a particular area of interest is proposed. The technology like Internet of Things (IOT) is included within the sort of solution which is outcome of merged field of computing and electronics. For monitoring the fluctuation of parameters like noise and pollution levels from their normal levels during this case the sensing devices are connected to the embedded computer system. For the need of continuous monitoring, controlling and behaviour analysis this model is adaptable and distributive for any infrastructural environment.

In this paper we discuss Natural Language Processing, normally abbreviated as NLP, is a part of computerized reasoning that manages the collaboration among PCs and people utilizing the characteristic language.A definitive target of NLP is to peruse, interpret, comprehend, and sort out the human dialects in a way that is significant.Most NLP strategies depend on AI to get importance from human dialects.deep learning strategies for language preparing and demonstrating.Improvement of factual language models assists with anticipating an arrangement of perceived words and phonemes, and can be utilized for improving discourse preparing and discourse acknowledgment.Be that as it may, right now the field of language demonstrating is moving from factual language displaying techniques to neural organizations and deep learning strategies.Thusly, one of the strategies for successful language demonstrating with the utilization of deep learning procedures is introduced in this paper.Introduced results concerns the demonstrating of the Polish language yet the accomplished exploration results and…

The construction industry continues to grow as the demand for infrastructure, homes, and office spaces grows by the day. Since the construction industry is so dynamic, it is vulnerable to a range of health risks. As a result, protection is a top priority in the construction sector to ensure a healthy working environment. Safety experts have determined that risky behaviours cause the majority of workplace injuries, and that controlling these behaviours is one of the keys to effective accident prevention and a low accident rate on construction sites. Safety in construction industry is much more important. This review paper is about to increase safety in the building industry performance. The study's primarily is to define the critical success factors that affect the implementation of construction safety management. This review paper is to recognize and solve major problems in the building sector with various solutions related to work situations that affect project safety performance. Due to lake of knowledge and awareness large number of people's deaths and long-term injuries occurs.…

An autonomous vehicle is a portable robot that combines multiple sensory navigation, intelligent decision making and control technology.This paper outlines the design of AGV control system, for controlling the longitudinal speed.In this way, a bicycle model is built to create a tracking problem and how to control the longitudinal speed in state space format.There are frictional forces that are considered while changing the velocity.PI and PID controllers are used for the speed control.By controlling the longitudinal speed of the autonomous car the results of the PI and PID controller are discussed.The relationship of speed and gas pedal position has also been obtained so as to make the journey jerk free.

Concrete is a construction material composed of Cement, fine aggregate, coarse aggregate, and water with or without admixtures.The concrete industry is one of the heaviest consumers of natural resources due to which sustainability of concrete industry is under threat.The biggest problem facing the concrete industry is the environmental and economic concern.In this research Paper , the Ordinary Portland Cement (Grade 43) has been partially replaced by Waste Glass Powder (GLP) and in Second stage Natural sand and cement replaced by stone dust and waste glass powder accordingly in the proportion of 0%, 10%, 20%, 30%, 40% & 50%, at constant 15 % of Waste glass powder by weight of M-30 grade concrete.Concrete mixtures were produced, tested and compared in terms of Compressive Strength, Split Tensile Strength and Flexural Strength of the conventional concrete at a period of 28 days.It is observed that glass Powder and stone dust gives better results as compared to conventional concrete .It is found that strength and workability of mixes increases significantly when glass Powder and stone…