The 100 most-cited articles in International Journal for Research in Applied Science and Engineering Technology, 2020

The high education system in Georgia currently is based only on the classical form of education, where the classrooms are led by the lecturers face-to-face with their students.Although the old system before 90-s could have lectures in the form of tuition by correspondence, this kind of system was cancelled.The modern system got under challenge when from March 02 of 2020 the education process was suspended in universities and schools countrywide due to the spread of COVID-19 coronavirus by the recommendation of national centre of disease control of Georgia.As previous practice shows universities would have to recover the missed classes in summer, or even in autumn that is a very uncomfortable period.As an alternative online interactive teaching was proposed using products that are part of G suite for education, such as Gmail, Classroom, Calendar, Forms, Jamboard, Drawings, Drive, Hangouts meet and free software Open broadcast studio.All of the products were tested.Paper includes the resolutions and recommendations for universities and colleges to quickly change the study form from…

According to data obtained by the World Health Organization, the global pandemic of COVID-19 has severely impacted the world and has now infected more than eight million people worldwide. Wearing face masks and following safe social distancing are two of the enhanced safety protocols need to be followed in public places in order to prevent the spread of the virus. To create safe environment that contributes to public safety, we propose an efficient computer vision based approach focused on the real-time automated monitoring of people to detect both safe social distancing and face masks in public places by implementing the model on raspberry pi4 to monitor activity and detect violations through camera. After detection of breach, the raspberry pi4 sends alert signal to control center at state police headquarters and also give alarm to public. In this proposed system modern deep learning algorithm have been mixed with geometric techniques for building a robust modal which covers three aspects of detection, tracking, and validation. Thus, the proposed system favors the society by saving…

Machine learning has various applications and one of them is healthcare.There should be much more advanced medical facilities so as to provide the best possible treatment for the patients[3].Also there are many machine learning algorithms (such as KNN, Random Forest and Decision Tree Classifier algorithms and many more) which were selected and on the given data many algorithms were applied so as to produce the best results.We can say that when machine learning implemented in healthcare can lead to a high increase in patient satisfaction.so this research paper, will try to implement functions of machine learning in health facilities in a particular system[8].Instead of directly performing treatment for the patient, if the disease is predicted beforehand using certain machine learning algorithms then the entire process of treatment can be made much more efficient[12].There are also some cases which occur when early diagnosis of a disease is not performed or carried out.Hence disease prediction is a really important step while treating the patient.As it is said "Prevention is better…

Worker wearing down is a circumstance looked by an association when the representative leaves the organization to join other association when he shows signs of improvement offer. It can likewise be named as Employee Defection. For the most part representative whittling down will be high when there is a squeezing need of workers in a specific industry because of mass retirements or development of association. At a certain point of time programming industry has confronted high whittling down rate by businesses because of enormous openings comprehensively in the product business because of the interest for programming items by all enterprises. Lessening the worker steady loss rate is a difficult issue looked by HR supervisors. This paper gives a definite perspective on foreseeing the representative turnover utilizing the Machine Learning algorithms. The forecast is finished utilizing the information sourced by IBM HR investigation. We utilized the Logistic Regression for the expectation and we got 85% exactness rate.

With rapidly changing computer and information technology and much of the technology finding way into vehicles, vehicles are undergoing dramatic changes in their capabilities and how they interact with the operators (drivers). Although some vehicles have provisions for deciding to either generate warnings for the human driver or controlling the vehicle autonomously, they usually must make these decisions in real time with only incomplete information. So, it is important that human drivers still have some control over the vehicle. So we propose a design for such System specially for vehicle to avoid the accidents due to drunken driving, low/high air in tyre's or an accidental fire in vehicle due to high engine temperature, accident(s) while parking & also this system controls the headlight & wiper of vehicle as per the environment condition.

Now a day the more interesting and attracting point in research area is synthesis of nanoparticles with specific properties. Due to unique properties of oxide of nanoparticles achieve great attention in research areas. It is widely used as solar energy conversion, catalysis, varistors, gas sensors, non linear optics etc. ZnO nanostructures obtained a great attention in the research area because ZnO has large band gap. There are many different methods for synthesis of ZnO nanoparticles such as sol-gel method, chemical vapor decomposition, thermal decomposition, hydrothermal method etc. Among this method sol-gel method is the best for the preparation of ZnO nanoparticle. Fabrication of nanomaterial by sol gel method is simple and also its have advantage to control the size of material and morphology study of the material. The main objective of this paper is synthesis of ZnO nanoparticle by sol-gel method and studies its characterization. In this zinc acetate used as precursor, methanol as solvent, NaOH used as medium. The obtained ZnO nanoparticles are homogeneous and consistent in…

In recent years, every e-commerce enterprise focuses on Customer Relationship Management(CRM) to provide the better services to the customer as compared to their competitors.Building a better relationship with customer help the enterprises in increasing profit and customers retention and satisfaction.It is necessary for enterprises to identify the potential customers in the market by mining the customer data to gain profitable insight.One of the efficient way to identify the different customer characteristics is by applying clustering analysis.In this paper, different clustering approach has been presented in order to segment the customer and apply the different marketing strategies accordingly.The possibility of hybrid combination of clustering algorithm can outperform individual model has also been discussed.

Steganography is a common term used for all methods for the inserting of extra secret content into some form of carrier, with the aim of securing of the introduced alterations. Now a days the art of transfer the secured information has got more observation and challenges. So, different techniques have been proposed for data hiding in different fields like LSB, RABS and others. This paper provides an analytical aspect of different existing techniques/methods of steganography where one of these is hiding of information on the bulletin board display. It uses the LSB technique over here.These methods can be further used to other means such as stadium, railway station or airport and other public places and even for officials.It also gives the overview of the methods like Watermarking, steganography-cryptography system which will be discussed.

Today's artificial intelligence has become a commodity of and experimental studies, such as mathematics.Machine learning is an application of artificial intelligence that allows machines to learn from prior data.The paper explains two modes of learning, supervised learning and unsupervised learning, used in machine learning.There is a need for these learning strategies if there is a kind of calculations are undertaken.This paper engineering narrates the supervised learning and unsupervised learning from beginning.It also focuses on a variety of Supervised learning methods and unsupervised learning methods.This paper sheds light on the basic construction of these two learning strategies.Comparative studies of Supervised and unsupervised learning have also been presented in the paper and allow the researcher to look more closely at these programs to understand which might be the solution to a particular problem.

Heart disease is the normal term used in the health industry. The meaning of the Heart disease is that the heart is not working properly or normally. In the medical terminology the heart attack is a condition where the supply of the blood to the organs of the body is blocked and then it will result into the blood clot. Now-a-days there are so many heart diseases like Coronary Artery Disease, Congestive Heart Failure and Bad Heart Rhythms etc. There are so many number of people who are suffering from the heart diseases. The heart diseases may or may not have the symptoms before it attack the people. So we need to predict the heart diseases for the people it effect or not. Now-a-days so much number of people is died suddenly due to the heart attack because the life style of the people is changed rapidly. In this research paper we use the Support Vector Machine which is the Machine Learning algorithm. The support vector machine is a supervised learning method. In the research paper the Support Vector Machine can predict the heart disease based on the given factors like sex, age, pulse…

A general term for conditions affecting the heart or blood vessels is called as Cardiovascular disease (CVD). It is commonly associated with an increased risk of blood clots and build-up of fatty deposits inside the arteries (atherosclerosis). Sometimes, it can also be associated with damage to arteries in organs such as the brain, kidneys, heart and eyes. CVD is the reason for the highest number of deaths globally and the major cause of death annually. Most cardiovascular diseases can often be prevented by leading a healthy lifestyle and addressing behavioural risk factors such as unhealthy diet and obesity, tobacco use, harmful use of alcohol and physical inactivity using population-wide strategies. Machine Learning can play an important role in predicting cardiovascular disease and such information, if predicted well in advance can provide significant insights to doctors who can then adapt their treatment and diagnosis for each patient accordingly. In the proposed research method, firstly the attributes are selected from the dataset, then data pre-processing takes place which…

The purpose of this study was to conduct online survey regarding students experience and perception related to online classes.Online platform has been a recent modification taken by the education system in India due the corona virus situation.Thus, this survey describes the opinion of school, college and university students with regard to online learning classes that have been made compulsory in the wake of corona virus situation.A structural questionnaire (Google form) link was sent to, colleges and university students WhatsApp, Facebook, and E-mail.The samples of 65 students are considered in this survey.This online survey method was used for data collection.The learners were used smart phone mostly for attending online lectures.Students also face many problems such as unfavorable environment for study.The finding shows that the following area plays an important role for students' satisfactions with online platform-class module, network issues, proper interaction and discussion with teacher and student.

This paper aims at reviewing existing YOLO architecture, its implementation and working.You only look once, is an architecture which is a regression problem.Yolo comes in different versions such as YoloV1, YoloV2 and YoloV3.The feature extractor for Yolo is Darknet.The network looks at the entire image only once.In one evaluation, a single neural network predicts bounding boxes and class probabilities directly from full images.The unified architecture is extremely fast.YOLO model processes images in real-time at 45 frames per second.Fast YOLO, an extremely fast version of Yolo, processes 155 frames per second.Yolo is better at making less localization errors as it looks at the entire image to predict objects on individual cells.This paper also provides details on the evolution and evaluation of the architecture.

In today's advance and sophisticated financial landscape, financial literacy is important because it doesn't only influence and impact upon financial decisions at the firm level but also a country's wider financial wellbeing and socioeconomic development.This study compares the financial literacy levels of urban areas by utilizing the results of the survey from the questionnaire developed by the OECD and by examining demographic and socio economic factors that influence the level of financial literacy.The results show that overall, the extent of monetary literacy in both areas is low and necessary measures should be taken by the government to extend awareness of monetary related matters.The literature findings also reveal that demographic, economic, social, and psychological factors are the most determinants, that some common themes appear with reference to the results of monetary literacy on investment decisions, demographic factors, methodology and program effectiveness, and that gaps exist in the literature of financial literacy in Urban area with respect to types of investment…

Air pollution is contamination of air with poisonous substance where the air is unfit to breathe and not only affect humans but also all living things in the environment 90% of the people in the world breathe polluted air at present air pollution is the thread to human life the entire pollution is affected by it.Some gases which causes air pollution are nitrogen oxide,carbon monoxide, carbon dioxide and sulphur oxide.The combusion of fossils at power plant and industries are responsible for air pollution.Sulphur dioxide which leads to heart disease and gases like carbon dioxide which leads to stopping of oxygen also leads to death thus to make human aware of air the air they breathe and to know about their environmental situation the proposed solution is used where an arduino which is attached to a gas sensor the gas sensor collects all the gases and transmits to arduino this stores all the value in cloud as soon as the value reaches high the user will receive an alert in webpage about the level of pollution in the particular area and also if the pollution level is to high an alert…

IoT (Internet of things) has become an emerging topic in technological field research.It is basically interconnecting of devices with each other over the internet network.It facilitates the digitalization and automation of the manually operating devices.We typically think of the Internet of things (IoT) in terms of autonomous cars and smart homes, but some of the best and innovative applications of IoT technology are in fields that are intensely practical.One of the major is health care monitoring system.The main purpose of our project is the luxury to explore improved services for patients and their handlers.It can be used to promote basic nursing care in the hospital environment by improving the quality of medicare and patient safety.Rural area is lack behind from the proper patient monitoring system.So, remote monitoring and guidance awareness by sharing information in an authenticated manner are the main objectives of our project.

The next major feature of the age of conversational services is chatbots in the new era of technology.A Chatbot framework is a software program that uses natural language to communi-cate with users.Chatbots is a virtual entity that can effectively explore the use of digital textual competencies with any hu-man being.Recently, their growth as a medium of conversa-tion between people and computers has taken a great step for-ward.The aim of the chatbot framework for machine learn-ing and artificial intelligence is to simulate a human conver-sation, maybe through text or speech.Natural Language Processing understands one or more human languages through chatbot software.To simulate informal chat communication, the chatbot structure combines a language model and compu-tational algorithms covering enormous natural language pro-cessing techniques.This paper discusses other applications that may be useful for chatbots, such as a computer conversa-tion system, virtual agent, dialogue system, retrieval of infor-mation, industry, telecommunications, banking, health, cus-tomer call centers, and…

In the past, Farmers often saw the availability of soil and influenced the allegations of improving crop varieties.They don't mind the humidity, the water level and especially the weather that threatened the farmer with the increase.The Internet of Things (IoT) is a practice to reinvent agriculture by empowering farmers with a broad range of strategies, for example, accuracy and practical farming to address challenges in the sector.Modern IoT changes help inform information on factors such as weather, temperature and soil fertility, Crop web based surveys assess water quality, soil moisture level, moisture condition and crop temperature.IoT helps farmers relate to where and how and where to stay.Remote Sensor Properties are used to monitor home conditions IoT development can reduce costs and stimulate normal growth productivity.

Heart disease is one of the most serious health threat growing among worldwide, for which mortality rate around the world is very high. Early detection of heart disease could save many lives, accurate detection of heart disease is crucial among the health care persons through regular clinical data and its analysis. Artificial intelligence is the effective solution for decision making and accurate heart disease predictions. Medical industry showing enormous development in using information technology, in which artificial intelligence play major role. In the proposed work, deep learning based approach on heart disease is done on Cleveland dataset. However existing studies are handled in Machine learning technique. The proposed work detects heart disease based in Convolutional Neural Networks. Experimental results shows our proposed work achieves high level of accuracy in prediction of heart disease.

Aromatic heterocycles are planar rings of atoms containing at least one non-carbon atom (N, S, O) and contains (4n+2)π electrons.A vast number of different classes exists for example pyrrole, thiophene, furan, pyridine, azoles, indoles, Isoindoles, quinolines, isoquinolines, Benzofurans, Isobenzofurans, benzothiophenes, Isobenzothiophenes, pteridines, purines.These ring compounds possess interesting pharmacological and biological activities which include: anti-malarial, analgesic, anti-inflammatory, anticancer, antifungal, antibacterial and are also used as pesticides: herbicides, fungicides, insecticides, rodenticides, and as stimulators and regulators of plant growth as well as fluorescence materials, ionic liquids, dyes and pigments.There are several established methods for their synthesis.This research paper aims at highlighting these very diversities of these ring compounds and the different methods by which they could be synthesized.

As in India agriculture provides employment opportunities for rural people on a large scale.It is an important source of livelihood and still our agriculture sector is facing challenges.And one of those challenges is productivity of land.Typically, collecting data from the field involves quite a bit of time.Currently, there is no such machine which can automatically test all required data.It is measured by collecting samples, sending to a lab, waiting days or weeks, and then only receiving a snapshot and report of the condition of field from that one day.As this is time consuming process and due to the lack of information about the nutrients present in soil farmers are not able to decide about crop, fertilizer and irrigation that would be best suited to the soil.Hence we need a portable device which can analyze the soil nutrients on real time basis.This research focuses on developing a comprehensive soil probe measuring everything from soil macronutrients (Nitrogen (N), Phosphorus (P), Potassium (K)) to soil moisture, pH and soil humidity.This research comprises of an electronic…

This study aims to investigate the potential hazards and accidents that might occur at Petrochemical industry.This research adopts HIRA to perform Hazard Identification and Risk Assessment in the workplace.This risk assessment tool will identify possible hazard involved in each task in every departments.HIRA is a proactive process to identify hazards and eliminate or reduce the risk of injury or illness to workers and damage to property.Once the hazard has been identified, risks involved will be estimated and categorized.If the estimated risk falls in a category, which is higher than the low risk category, then possible control measures will be recommended.HIRA is a method by which we try to identify the main hazardous substance and then try to reduce the effect of the hazard.

Every day, every women, young girls, mothers and women from all walks of life are struggling to be safe and protect themselves.In our country even if India is growing day by day but still there are many crimes happening against women.The streets, public transport, public places in particular have become the dominion of the hunters.In this paper, a smart security wearable device for women based on Internet of Things is proposed.It is implemented in the form of a smart bracelet and comprises of Raspberry Pi Zero, buzzer and switch to activate the services.In this, we just have to press button and system will send current location to friends, family and police.Our proposed system resulted in robust, flexible, low cost and user friendly system to solve the problem against women which help them to live independently or freely.

Because of the mechanical, cultural, ecological and economic advantages of concrete production is important.Consequently it is very beneficial to accomplish the aim of sustainable building using waste material in concrete.Thus this thesis aims to use waste ceramic tile aggregates in concrete manufacturing as an alternate source to coarse aggregates.Owing to its uses in processing, ceramic waste rises day by day, so the ceramic industry needs to recover, reuse and repair concrete products to reduce the waste dump from ceramic factoriesIn this analysis, consistency testing on the strength factors of the concrete mix is obtained by fractional substitution of the cement with the material of Ceramic Tiles.Since ceramic tiles powder is used in various forms of building work, ceramic tiles powder is often used as a partial substitute for cement as a material test was conducted to determine the power and quality of the concrete mix with ceramic tiles powder in several amounts, varying from 5 % to 20%.Ceramic Tiles Powder added 5 %, 10%, 15% and 20% cement to the concrete mix and then added…

Roads make a crucial contribution to the development and economic growth, bringing considerable social benefits.Roads are paramount for growing and developing a country.Roads are opening up more areas and improving social and economic development.The location of design for highway's centerline on a surface is called alignment.Alignment's primary requirement is to be short, easy, safe, and economical.Horizontal alignment, vertical alignment, and cross-section are the three main parts of geometric design.This paper shows a typical design of roadway with the support of AutoCAD Civil 3D.AutoCAD Civil 3D design software helps in a comfortable and relaxed way to achieve design.Civil 3D design is simple and easy to grasp to build alignment, AUTOCAD civil 3D uses the topography and survey data collected from LIDAR or similar technology.Once the alignment has been demarcated, the geometry can be tested and evaluated using the IRC standard and requirements using The civil 3D built-up software.Once horizontal geometry has been achieved, vertical geometry can also be optimized.Civil 3D uses…

The results of Internet of Things (IoT) collapse can be drastic, therefore, the study and analysis in security problem in the IoT is of extreme significance. Principle target of IoT security is to safeguard protection, classification, guarantee the security of the clients, frameworks, information. Thus, research in IoT security has recently been gaining much momentum now days with various platforms. In this paper we provide ensuring security of data exchange, IoT architecture and IoT Security architecture, applications, drawbacks of IoT. We study about various security issues, Problems, normal and Denial of service attacks, issues and research defy in IoT are also discussed.

Primary Objective of this study is to discuss the effectiveness of COVID-19 on air pollution.We have collected data from NASA, ESA (European Space Agency) and CPCB online portal for air quality data dissemination.The satellite images from the above mentioned agencies elucidate that quality of air has improved causing reduction in the air pollution during COVID-19.It was observed that Nitrogen Dioxide content was decreased in the air compared to same period last year.It suggests that COVID-19 lockdown mitigated air pollution across the globe.We will discuss data of nitrogen dioxide content this data in paper, and how much air pollution was controlled due to this lockdown.I.

Agriculture is the basic source of food supply in all the countries of the world-whether underdeveloped, developing or developed. Not only providing food, this sector has contributions to almost every other sector of a country. According to the Bureau of Statistics (BS), 2017, about 17 % of the country's Gross Domestic Product (GDP) is a contribution of the agricultural sector, and it employs more than 45% of the total labour force. In the decreasing crop production and shortage of food across the world, one of the crucial criteria of agriculture now-a-days is selecting the right crop for the right piece of land at the right time. Hence, in our research we have proposed a method which would help suggest the most suitable crops for a specific land based on the analysis of the data of previous soil series classification using machine learning. In our work, we have implementedBagging Classifier, Support Vector Machine, and k-Nearest Neighbour for soil classification and crop recommendation.We have trained these algorithms with the training data and later these were tested with test…

Climate change has affected the weather forecast on a regular basis compared to reality.Meanwhile, weather forecast plays an important role in daily life and especially it affects developed countries in agricultural fields around the world.When we apply information technology software, we can assess the general weather condition of a given city, and with the help of recent modern scientific methods for more accurate analysis and prediction of weather based on those collected weather data for a period of a week earlier or longer for future weather forecasts.Therefore, in this study, machine learning model was applied and it was allowed to study methods and feature engineering from data pre-processing, so through this, we find an unpredictable model of climatic conditions, a prognostic model is also monitored.For this work, various weather parameters were collected from the national climate data center through available software applications, with the application of the Long Short-Term Memory (LSTM) model is an artificial recurrent neural network (RNN) were trained for different…

Today, the major problems that cities face is that of traffic.Empty roads are becoming a luxury nowadays.Heavy traffic eventually means high waiting time at the traffic signal.The traffic light timers at squares are set according to the average amount of traffic flow at these squares.This results in traffic congestion at certain junctions due to sudden changes in traffic density.These sudden changes in traffic densities resulting in the need for a smart system that could efficiently handle traffic congestion based on the density of traffic.This paper discusses some of the existing traffic light control systems, their drawbacks as well as our proposed system where we are trying to avoid the drawbacks of existing systems.The main motto of our project is to provide a smooth flow of traffic and to reduce the time duration for which one has to stand at the traffic signal.We have achieved this by using raspberry pi processors and pi cameras corresponding to the four traffic lanes.The cameras will monitor the density of vehicles of standing at the signal using image processing.In addition…

The Internet of Things (IoT) could also be a network of connected vehicles, physical devices, software, and electronic things that facilitates data exchange. The aim of IoT is to provide the IT-infrastructure for the secure and reliable exchange of "things." safety of this knowledge could be a difficult task; but, security challenges will be lessened with cryptography and Steganography techniques. These techniques square measure crucial once addressing user authentication and knowledge privacy. Within the planned work, the elliptic Variety Galois cryptography protocol is introduced and mentioned. During this protocol, a cryptography technique is employed to encode confidential knowledge that came from totally different medical sources. Next, a Matrix XOR coding Steganography technique is employed to embed the encrypted knowledge into an occasional complexes image. The planned work additionally uses associate optimization algorithmic rule is a known as adaptation Firefly to optimize the option of canopy blocks among the image. Supported the results, varied parameters square measure…

Material with unique metallurgical properties such as Titanium, Haynes-25, Molybdenum, Columbium C-103, hardened steels, and other superalloys was developed to meet the demands of extreme applications in aerospace, automobile, and nuclear reactor industries. Machining these materials using a conventional machining process is a challenging task. Electrical discharge machining (EDM) is one of the most suitable non-conventional processes to achieve precise quality components with optimum tooling cost. EDM process becomes a natural choice for machining of superalloys; its low machining removal rate and poor surface quality have been the key problems restricting its development. To overcome these drawbacks, the nanopowder suspended dielectric oil is used, which increases its conductive strength and increases the discharge gap between the tool and workpiece. This newly developed material removal process is called Powder Mixed Electrical Discharge Machining (PMEDM). This paper presents the review work done to improve the performance characteristics of machining like MRR, TWR, EWR, SR,…

Identification of brain tumor is a highly difficult task in early life stages. The presence of brain tumor among humans has increased in large amounts in recent years. Gliomas are one of the most common types of primary brain tumors that account for 30% of all human brain tumors and 80% of all malignant tumors. The World Health Organization (WHO) specified rating system is used as a basic method for medical diagnosis, prognosis and life. The main ideology is to propose and develop reliable, typical methods for detecting the brain tumor, extracting its characteristic and classifying the glioma using Magnetic Resonance Imaging (MRI). The model developed automatically assists in brain tumor detection and is implemented using image processing and artificial neural network. Detecting the tumors at starting point is very critical for a patient's healthy life. There are several literatures on identifying these kinds of brain tumors and enhancing the precision of detection. This method use Convolutional Neural Network algorithm to estimate the severity of the brain tumor which gives us…

Fused convolutional neural network for white blood cell detection helps us to detect white blood cells including their subtypes by using Convolutional neural networks and deep learning algorithms.Deep Learning has already shown power in many application fields, and is accepted by more and more people as a better approach than the traditional machine learning models. In particular, the implementation of deep learning algorithms, especially Convolutional Neural Networks (CNN), brings huge benefits to the medical field, where a huge number of images are to be processed and analysed. This paper aims to develop a deep learning model to address the white blood cell classification problem, which is one of the most challenging problems in blood diagnosis. A CNN-based framework is built to automatically classify the white blood cell images into subtypes of the cells. Experiments are conducted on a dataset of 13k images of white blood cells with their subtypes, and the results show that our proposed model provide better results in terms of evaluation parameters.I.

In this paper, we apply a convolutional neural network (CNN) to the tasks of detecting and recognizing food images. Because of the wide diversity of types of food, image recognition of food items is generally very difficult. However, deep learning has been shown recently to be a very powerful image recognition technique, and CNN is a state-of-the-art approach to deep learning. We applied CNN to the tasks of food detection and recognition through parameter optimization.We constructed a dataset of the most frequent food items in a publicly available food-logging system, and used it to evaluate recognition performance.We also implemented a set a labels for each food item which describes the nutrition content such as carbs, calories etc. CNN showed significantly higher accuracy than did traditional support vector machine based methods with handcrafted features.In addition, we found that the convolution kernels show that colour dominates the feature extraction process.For food image detection, CNN also showed significantly higher accuracy than a conventional method did.

The paper aims at the overall review of planning, development and thus fabrication of the multipurpose agriculture robot which is able to dig the soil, leveler to shut the mud, sprayer to spray water and fertilizer separately, these whole systems of the robot works with the battery, and therefore, the alternative energy.Quite 40% of the population within the planet chooses agriculture due to the first occupation, in recent year the autonomous vehicles within the agriculture has experienced increased interest.The vehicle consist of Relay switch and Bluetooth.This language input allows a user to interact with the robot which is familiar to most of the people.The agriculture robot works on solar energy.The advantages of these robots are hands-free, and fast data input operations.In the sector of agricultural autonomous vehicle, a concept is being developed to investigate if multiple light compact autonomous machine may be more efficient than traditional large tractors and human forces.Hence, the device is to be designed which helps farmers to beat the stated problem.It's geared toward…

The heart is a significant organ of the human body.These days heart disease has become an important issue in humans, nearly one person dies per minute.To deal with this problem we need a strong prediction system for this condition. Machine learning is used to solve many data science problems. The traditional use of machine learning is to predict an output from input data. Here machine learning is applied to medical records to predict the diseases of each patient. The ML algorithms learn patterns from the given input data. And using them with real-life data to forecast the disease's existence. Some machine learning algorithms predict with great accuracy while others predict with insufficient accuracy. Here we predict heart disease patients in the early stage by interpreting the medical records accurately and compare the algorithm accuracy. In this research paper, we checked and compared various machine learning algorithms, such as decision tree, logistic regression, k-nearest neighbors, support vector machine, gradient boosting. We Used the UCI heart dataset and for the…

Machine learning is one of the most exciting technology& it gives the computer that makes it more similar to humans .It is actively being used today, perhaps in many more places than one would expect.Learning is a natural human behaviour which has been made an essential aspect of the machines as well.There are various techniques used for the same.Traditional machine learning algorithms have been applied in many application areas.This paper presents the most commonly used machine learning algorithms such as supervised, unsupervised, reinforcement.In each of our study we found that the results of various machine-learning algorithm depends on application areas on which they are applied.Our review of study not only suggests that these techniques are competitive with traditional estimators on one data set, but also illustrate that these methods are sensitive to the data on which they are trained.

Medical diligences generate a huge amount of data. Cardiovascular Disease is becoming a common disease leads to death now a days. Hence it is important to predict as early as possible. Heart disease data are stored in a database in large amount. Different Machine Learning techniques (SVM, Logistic Regression, Neural Network, KNN, RF, Naïve Bayes, DT, and GDBT-Bagging Tree) can be used to classify the data in the database. This paper concentrates on various ML techniques that are used to predict the heart disease by using dataset. The accuracy, sensitivity, specificity and Area under Curve (AUC) are calculated for various techniques. The result shows that Artificial Neural Network (ANN) algorithm with SAE produce the highest accuracy of 90% respectively. Ensemble method of techniques is also used to improve an accuracy of heart disease.

Attacks on the Automated Teller Machine (ATM) has increased dramatically over the past decade which has inspired the utilization of biometrics with picture for individual distinguishing proof to obtain elevated level of security and precision. The task depicts a framework that replaces the ATM cards and PINs by the physiological biometric unique finger impression confirmation and face acknowledgment. Also, the element of one-time secret key (OTP) bestows security to the clients and liberates him/her from reviewing PINs. In this framework during enlistment the authentic client's unique finger impression and face is held in the database. The procedure of exchange starts by catching and coordinating fingerprints and face designs. The framework will naturally recognize genuine real attribute and phony examples. A GSM module associated with the Microcontroller will send a 4-digit code (OTP) created by the framework to the enrolled portable number. After the substantial OTP is entered the client can perform banking exchange. In any sort of phony access endeavors the record is blocked and…

Blockchain is a distributed, decentralized, public ledger for securely exchanging digital currency and transaction information.Blockchain was invented in 2008 by satoshi Nakamoto as public ledger for cryptocurrency bitcoin.Blockchain allows the participants to verify the transactions independently.This paper explains the concept of blockchain, characteristics, how blockchain works, and its security mechanisms.It attempts to highlights role of Blockchain in various fields.Key aspects: Improved accuracy by removing human involvement in verification.Cost reductions by eliminating third-party verification Decentralization makes it harder to tamper with.Transactions are secure, private and efficient.Transparent technology.I.

The distance and related concepts like eccentricity, radius, diameter, center, periphery, etc. were already defined and used in many applications of graph theory.In this we paper, we investigate the idea of Fuzzy distance, which is a metric, in fuzzy graphs.The concepts of eccentricity, radius, diameter, centre and self centered fuzzy graphs are studied using this metric and some properties of eccentric nodes, peripheral nodes and central nodes are obtained.We will show that any complete fuzzy graph can be embedded as an induced subgraph of a self-centered fuzzy graph.

Image captioning is a complicated research area of Arti cial Intel-ligence (AI) which requires a functional and robust model that generates a caption for any image. Image captioning is a fundamental task which requires not only semantic understanding of images but also the interactions between the objects present in the image.Another task is to understand the visual lan-guage dynamics and to translate these relations into sensible captions . In this paper , we have proposed an architecture employing the use of multilayer Convolutional Neural Network (CNN) which is used for image processing and extracting features from the image. It generates an embedding which repre-sents the image which is passed to Long Short TermMemory (LSTM) to accurately structure meaningful sentences using the generated keywords .We showcase the accuracy of our model using Flickr30K dataset which contains 31,783 images with 5 captions for each image.We show that our model gives better results using the bleu metric.

COVID-19 is a virus part of corona virus family that causes a range of familiar disease from the common cold to SARS, COVID-19 is referred as novel corona virus because it is new to human. According to virus it spread from one person to other person through contact. So research public health practices and guidelines, one of the tool to our society can use to understand the disease is Geographic information systems (GIS) provide the utilization ,easy access and manipulation of geospatial information. The main advantage of GIS is mapping the many different locations of country and other facilities with human on a dashboard which helps in better monitoring and surveillance. Also, detailed studies are possible with respect to diseases forecasting, prediction of outbreaks, identification of disease cluster or hotspot and to evaluate different strategies to prevent the spread of infectious diseases. Geospatial industries have come to rescue in a lot of crises and disasters by boosting relief and rehabilitation efforts. In the case of COVID -19 geospatial communities is proactive in…

Coronavirus (COVID-19) is the biggest crisis in the world in last 75 years.The pandemic set foot in India from Wuhan, China.Seeing the peril of this virus the Indian Government had announced complete lockdown in the country from 25 th March, 2020 to 14 th April, 2020.The lockdown was further extended till 3 rd May and with the number of cases shooting upward the government had to increase it further till 17 th May, 2020.In this research paper the impact of coronavirus on Indian Economy is discussed.An attempt is made to have a sector wise research on the impact of COVID-19.The sectors include Aviation, Hospitality, Agriculture, Chemical industry, Electronics etc. Impact of COVID-19 on imports and exports is also stated.How coronavirus has affected the unemployment rate in the country has also been discussed.In the end the current article also seeks to suggest the different ways in which the situation can be overcome.

Many of us who use smart phones incline towards reading information via social platforms over the web. The news platforms are broadcasting the information and deliver the basis of validation. The issue is how to validate the information and articles which are dispersed between social platforms like Twitter, WhatsApp groups, Facebook Pages along with many different social interacting sites. It is unsafe for the humanity to consider such reports and pretend to believe it as an authentic information. The longing is to discontinue the rumours specially in the evolving nations like India, and concentrate on the truthful news articles.This presented approach displays a model for discovering fake news, along with the support of Machine learning and natural language processing.We use a corpus of labeled real and fake news reports to make a classifier that can come up with conclusions about data built on the content from the corpus and use a text classification method, using four distinctive classification models, and explore the outcomes.

The creation and introduction of the Internet to the world in the mid 90's has played a huge role in impacting the way we live.It cannot go unnoticed that presently the world is evolving and at a fast pace.This evolution can be seen when we look at the way we do some basic activities now compared to how they were done before.From the way we work, our manner of driving and even the process of making purchases have evolved into easier methods.This is as a result of the Internet of Things.The Internet previously used to be about people networking between and among people but it has now transcended into things networking between and among people or other things.In other words, we can refer to the context of the Internet as a relationship or connection between people to people, people to things and things to things.Highly developed chips and sensors that carry valuable data are embedded in almost every tangible thing that surround us.This study aims at reviewing the various technologies that enable the Internet of Things, the challenges they are likely to face and suggest research issues.

Artificial Intelligence is a technology that plays a major role in education.Nowadays AI is a part of our daily life.Many educational organizations work with the government to implement better AI facilities in education.In this paper, I argue that the human teacher is better than the robot teacher.Lack of human contact is the main issue with robot teachers.Robots are advanced but can't replace teachers instead of this if we can use a voice assistant as a teacher assistant.Voice assistants like Alexa, Siri, Amazon Echo can be used by teachers.Voice assistant able to record audio, can make calls, send messages, give GPS information.The main approach of this paper is to help teachers in their routine work, so teachers can more concentrate on students' progress.

Our country (India) is the second largest population of world; according to that vehicles are increased day to day life.Here, the questions arise!how to avoid the congestion in the road; that means traffic management.Traffic management has since quite a while ago existed in some frame, from the beginning of railroad flagging or movement lights on city lanes, yet the improvement and execution of modern coordinated applications in light of Intelligent Transport Systems (ITS) has developed apace lately, because of effective research and technological advances.Develop a system which can be used to predict high level of traffic congestion using data collected from live video stream analysis sensors image processing traffic congestion system can utilize the power of cloud computing and the strength of artificial neural networks traffic is increasing in every major city, which raises an average commute time.Los Angeles has the highest time lost in traffic congestion and parking search while minimizing implementation costs and requirements of maintenance.

Brain tumor is the deadly cancer.It can occur at any age.World is worrying about brain tumor, almost survival chances of affected human being is very less.However it is possible to recover from the brain cancer, if it is detected early stage.For the purpose of recognition or detects of tumor, deep learning is used in the field of medical research.Deep learning has become the important method for complex tasks such as image classification and object detection.Here, we used MRI kaggle dataset downloaded by internet.CNN is the most popular neural network model used for image classifications.Keras was designed to enable fast experimentation with deep neural network.Here we used Tensor flow and python programming environment for the development of our proposed system.This system is more applicable in medical sector.Within this proposed method we used fully automatic segmentation and feature extraction of brain tumor detection and classification using CNN techniques.

This paper outlines a remote monitoring system of temperature, humidity, gas and light control for cold storage warehouses.In these warehouses, it is significant that homestead produces should stay fresh.Lamentably when an administrator goes out from the cold storage, the temperature and other ecological factors like humidity, gas and light could be changed because of the different reasons, for an instance a valve of cooler is broken.This temperature change can bring about a major issue about the nature of farm produce. To overcome this issue, the owner needs to look to the present condition of the temperature and different ecological factors of the cold storage, even when he is far away. In this way, a monitoring system is required to display and control the ecological factors, for instance, temperature, humidity, gas and light when the owner is not present in the warehouse. Hence, this paper depicts the remote checking of warehouse, where this monitoring system is put on line follower robot setup to ensure complete tracking of the environmental condition of the warehouse. The…

The current study reveals the documentation of traditional use and ethno-entomological value of Red weaver ant in Mayurbhanj district with special reference to tribal health and safety prospective.The traditional information are collected through questionnaires in six selected zones of Mayurbhanj district.The resident tribes of this district commonly use this species as a delicious food and traditional medicine to treat different aliment in their daily life.The brood of this arboreal species is mostly found in tropical fruit plants.This species is mostly consumed in the form of a Chutney in daily diet.The tribes use this species as medicine in different disease like common cold, fever, Jaundice, enteric problems, Whooping cough and to increase the hungriness.The Rairangpur has the maximum dietary value, ecological value and economic use i.e. 83.54%, 68.99% and 79.11% respectively and highly defensive in nature.In Udala area 79.19% people are mostly use this species as medicine in traditional treatment and 67.79% informants are having cultural beliefs towards this species.The tribes…

Industry should have safety for coal mine industry. Underground mining risk include suffocation, gas poisoning , object fall, and gas explosion , so air quality and dangerous event detection is very important in mining industry. Base station observe the underground mining by wireless network of real time situation. It provides real time monitoring of harmful gases like CO(carbon dioxide), METHANE,BUTANE, LPG and SMOKE and also DHT11 (humidity and temperature). The reason behind death of miner is due to improper treatment is provided them. By any reason if any person is fall down the emergency alert will beep. For this reason worker should wear helmet , many workers are not aware of it. The transmission of data in coal mine we will use zigbee technology. Mining system is based on capable wireless network. Smart helmet is developed for reducing difficulties in coal mining area in observation of real time monitoring of harmful gases.All these harmful gases are detected by gas sensor, humidity temperature sensor, and cross checked by some limits.Then the device will alert the buzzer…

A report compiled by the World Health Organization in 2013 stated that 35 percent of women around the world had been victims of sexual violence [1].Mostly, victims are able to reach for help when they are in risk, but we can aid her before any incident happens.In this paper we propose a system where we will pre notify the user about the red alert areas where she will be going. Our system will track through GPS [1][2][3][4][5] which will find out their current location and inform them about the place being vulnerable. This paper introduces a mobile application called SWMS (SafetyApp for Women: a non-Magnanimous Shield) that provide an essential feature to place an emergency help.

With the rapid change and development of science and technology of today's world, new methods and techniques are used to meet the interests and demands of the 21st-century learners.There are problems encountered in teaching science that requires exploration in learning.A quasi-experimental design was utilized in the study.The sample consisted of 83 seventh grade students.The standardized test was the instrument used to measure the academic performance of the respondents.Of the groups in the study, the experimental group was taught using PhET Interactive Simulation-Based Activities, while the control group was taught using the traditional teaching method.The results revealed that the academic performance (pre-test) of the control group (M= 13.28) is slightly higher compared with an experimental group (M=14.26),but there is no significant difference between their academic performances (t=1.99,p>.05).After the implementation, the academic performance of the control group increased from (M=14.26 to M=22.65).However, considering the remarkable increase in the academic performance of the…

One of the most researched topics with wide implementations in different fields is Handwritten Character Recognition (HCR). To utilize this technology in automated data-entry applications, this is one of the fields on which past and recent works have been done to focus on a variety of languages. Individual characters in a word are recognized through a set of images, which are then studied by the Deep Neural Network. It is with the help of this recognition that results are ranked. This ranking is performed based on the client's request. A Convolutional Deep Neural Network Model is considered to acknowledge the handwritten characters in this paper. It learns, using local receptive areas and heavily connected neural network layers, a useful set of ordination which are required to generate an optimum result.

Pre-stressing and arrival of more-strength material permit constructions of much lean floors slab with least value with natural frequency along with damping. Within some circumstance, vibration because of forcing frequency due to normal man activity can be annoying to occupant. Since the occupant is counted both sources and the sensors, the vibrations can't be isolated and should control by the structural systems. In recent time, there are limit knowledge related to the overall dynamic characteristic of concrete-slab, even including contribution of individual structural along with non-structural component. The programme of modal testing related to slender one-way spanning with 50 percentage scale post-tensioned concrete slabs are reported. Test is carried out by utilization of electro-magnetic shakers, instrument hammers, heel-drops, and walking-excitation, to check all floors dynamic characteristic. With the help of this test, we investigate the effects on vibrations performances of the levels of pre-stress, and even of non-structural addition, which even include vibrations…

This article provides a comprehensive introduction about the Lean Manufacturing Systems or also known as Toyota Production System in Japan. First, the paper gives an introduction to TPS, followed by a brief Literatures Review on all the papers referred for the conception of this paper. The two fundamental pillars of TPS are discussed later on with a description of each pillars in depth. The next section deals with the 7 wastes of lean followed by the benefits of implementing TPS and the barriers to successful TPS implementation. The literature review framework in this paper provides a clear overview of the To0yota Production System, which can be used as a starting point for further research work.

Placement of students is one of the most important objective of an educational institution. Reputation and yearly admissions of an institution invariably depend on the placements it provides it students with. Institutions make great efforts to achieve placements for their students .This will always be helpful to the institution. The objective is to predict the students getting placed for the current year by analyzing the data collected from previous years students. This model is proposed with an algorithm to predict the same. The data has been collected by the institution for which prediction is going to be done and by applying suitable data pre-processing techniques. This model is prepared by using Logistic Regression algorithm. This algorithm independently predict the results and we then compare the efficiency of the algorithm, which is based on the dataset. This model will helps the placement cell to focus on the potential students and help them to improve their technical and social skills.

This paper is on the Smart car parking system.In which we going to use the IR sensor to detect the vehicle and it will help the owner to find a convenient parking spot.This project will help to resolve the parking problems.Parking spaces are very important in metropolitan cities.Because of the increase in large no. of vehicles, the need for parking spots is a necessity.And hence an urgent need to develop a system that can manage these parking spaces.So, our project's objective is to develop a system to indicate the vacant lane in the parking slots.This involves a system that includes an infrared sensor and Arduino in every lane and a led display outside the car parking gate.Parking slots are monitored by the staff of the concerned authority.The paper includes the details of components that are used and about the working of this system.The paper also contains the future scope of this project which will lead our nation towards the transformation.

The project presents the concept, functional physical model of an air purification system for small public spaces or apartments.The purifier is controlled by a microcontroller of the Arduino UNO series.The model is equipped with a set of sensors which are used to determine the air quality.After exceeding the adopted threshold in the software, the system automatically starts the process of air filtering.The air purification system depends on the optical dust sensor readings as it senses the quality of air in the room and turns the air purifier On and Off accordingly.The body of the air purifier is made by wood and filters.The filters used are pre-filter, dust-filter & fine-filter.The purifier absorbs solid pollutants and reduces VOC pollutants.The system has been equipped with an LCD screen informing the user about the air parameters and the quality of air being purified.

In this paper author is describing concept to identify species of birds by using python Tensor Flow and Deep Learning algorithm. Earlier technique were using birds Voice or Videos to predict it species but this technique will not give accurate result as audio may contains background or other animal Voices. So images can be best option to identify species of birds. To implement technique this we need to train all birds species and generate a model and then by uploading any image deep learning algorithm will convert uploaded image into gray scale format and apply that image on train model to predict best match species name for uploaded image. To train bird species we are using 'Caltech-UCSD Birds 200(CUB-200-2011)' dataset which contains 200 species or categories of birds. Model will be built using that dataset and tensor flow deep learning algorithm.

First principles based DFT calculations performed to insight structural and electronic properties of Boron doped Magnesium atom decorated graphene sheet for application of hydrogen storage.The four H 2 molecules stably binds magnesium atom with Boron doped graphene sheet.The average binding energy extracted in the range-0.566 to -0.687 eV/H2.Partial density of states of complex system shows s and d orbitals of H 2 molecule and Mg atom at -0.1eV overlaps of main peaks indicates strong hybridizing and binding of s and d orbitals of H 2 and Mg atom respectively.HOMO & LUMO study shows stability of complex system.DOS investigation reveals the electronic density of states of complex system.

Agriculture is back bone of economy for most of the countries.In India, 50% of our population is dependent on agriculture field.According to NITI Aayog CEO Amitabh Kant, India cannot achieve 9-10 % GDP growth without revolution in the farm sector for next 30 years.Agriculture sector is seeking innovation for improving crop yielding because of unpredictable climatic changes, the rapid increase in population growth and food security concerns.And specially in the pandemic situations there is need of quality of food for perfect nutrition.As to reach the increasing demand for quality and quantity of food, there is need of Artificial intelligence-based technology in agriculture.So, in order to increase production with quality we need to adapt to AI based application such as precision farming, disease detection, smart sprayers with help of deep learning algorithms, image processing, artificial neural network (ANN), convolutional neural network (CNN), sensors, wireless communication systems.With help of technology we can effectively use chemicals and reduce expenditure.As a result of this,…

Stock market prediction is one of the most important things in financial world as it decides the flow of a company towards profit or loss in future. Prediction of a stock value of a particular entity or a company is a tough and difficult thing to do. Since early 1980 s investing money into the companies by taking some of its stock had become a big thing (trend). After 2000 s some Machine Learning, Artificial Intelligence concepts were introduced to make prediction a stock value. There are many Machine learning models such as Support Vector Machine (SVM) model, Regression model, LSTM model, Artificial Neural Network (ANN) etc. had used to make predictions by considering previous year data as sample. By far SVM model has shown most positive results by predicting stock value accurately. Since all this models were tested on little quantity of particular data set, if we take large amount of data (previous) as input then it will bring more accuracy in prediction. Also by considering Financial NEWS articles, Social Media trends, Company's work ethics and taking all this variables as input…

In Current scenario, skin maladies are the most widely recognized medical issues.More than 90 percent World Population get infected by skin disease at some point.It is also observed that Skin Diseases get increased with age and were more frequent in men than women.In this article, we are focusing on dermatological department of Health industry.We have utilized picture handling for include extriction and feed forward ANN system for approval reason.The framework worked in 2 stages -1.Pre-processing of the colored skin image for feature extraction 2. Identification of disease.The framework effectively identifies 6 unique sorts of the dermatologicall skin disease with exactness pace of 95%.

Nadarajah and Haghighi has defined the extension of the exponential distribution we have called this as NHE distribution.It is continuous probability distribution with a wide range of applications such as in life testing experiments, reliability analysis, applied statistics and clinical studies.However, it is not flexible enough for modeling heavily skewed datasets as compared to modified distributions.In this study, we have generated a new continuous distribution having three parameters based on the half logistic-Generating family called half logistic NHE.The structural properties of this model are explored such as the probability density, cumulative density, hazard rate, reversed hazard rate, and quantile functions.The model parameters are estimated using the three well-known methods namely maximum likelihood estimation (MLE), least-square estimation (LSE) and Cramer-Von-Mises (CVM) methods.Further, we have computed the Fisher information matrix and asymptotic confidence intervals for ML estimators.The potentiality of the proposed distribution is also evaluated by fitting it in…

The project proposes an associate degree IOT (Internet of things) that monitors the important time behaviour of the driving force, to overcome the accident occurred because of asleep driving. The face, a very important part of the body, conveys a great deal of knowledge. Once a driver is in a state of fatigue, the facial expressions, e.g The frequency of blinking and yawning, are completely different from those within the traditional state. The device that detects the drivers' fatigue standing like yawning, blinking, and period of eye closure, mistreatment video pictures. We introduce Haar Cascade face tracking algorithmic programs to enhance the chase accuracy. Further, we have a design replacement detection technique for facial regions supporting sixty eight key points. Then we have a tendency to use these facial regions to gauge the drivers' state. By combining the options of the eyes and mouth, the device will alert the driver using an alarm.

Automatic face recognition technologies have made many improvements within the changing world.We have find a real world solution for automatic student attendance system in a classroom using Real-Time Face Recognition.In order to reduce the human computation, our system are going to be recognizing human faces fast and precisely in images or videos that are being used for further face recognition.Here we use the opencv library dlib for face recognition.Further the label corresponding to the recognized image, which is the student name, is provided with attendance, else the system marks as absent.

The aim of this project work is to propose a speech emotion recognition method based on speech features and speech transcriptions (text). Modelling emotional behaviours is a challenging task due to the variability in perceiving and describing emotions. We try to perform emotion analysis on the speech by collecting speech and textual features and applying a deep neural network model which can classify the sentiments of the speech. Ideally, we would like to experiment with several deep neural network models which take in different combinations of speech features and text as inputs. Speech features such as Mel-Frequency Cepstral Coefficients (MFCC) help retain emotion related low-level characteristics in speech whereas text helps capture the semantic meaning, both of which help in different aspects of emotion detection.

The present study emphasis on the importance of management information system which forms the backbone for digitalizing the organization.It comprises of information useful for smooth functioning by evaluating and synchronizing both hardware and software technologies.The management information system has gained popularity in last few decades with almost every sector has implemented its principles to manage the economic flow and functioning.It has greatly influenced the world connectivity with business point of view and has uplifted the management strategies.The presented mini review describe the elements and usage of management information system along with its advantages.The study provides, insight on the category of management information system with its possible applicative sectors.

The bone of contention for Advanced Driver Assistance Systems (ADAS) is Lane Detection. It is not effectively executed and is challenged because of susceptible computer vision techniques which are vulnerable for many factors like peculiar road pattern, unusual lighting and weather conditions, repercussion of obstacles like shadows and other cars, and many more. To try and overcome these vulnerabilities, The Sliding Windows method is used in this paper to detect lanes in real-time using the OpenCV python package. It includes undistorting, preprocessing, detecting lanes on the perspective transformed frame, and displaying detected lane as output. Radius of curvature of lane and offset of the car from the center of the lane is calculated. During preprocessing, different edge detection methods like Laplacian, Sobel and Canny edge detection methods are examined. After comparing and contemplating, it is deduced that Canny edge detection is better than the remaining ones. The test videos for lane detection are taken from Udacity GitHub repository.

Plant disease detection system has been a necessity for cultivators as detection of a correct disease might lead to a proper yield and effective growth of the plant.The proposed plant disease detection methodology aims at identifying tomato plant diseases from digital images of affected plant leaves.This proposed technique will help farmers or any tomato cultivators to detect plant diseases digitally as the same process manually might lead to incorrect detection.In the proposed project, various image processing steps are performed on the leaf images along with classification methods such as K-Nearest Neighbor Algorithm and Naïve Bayes algorithm to distinguish between different plant diseases.

Malicious Uniform Resource Locator/malicious websites are a high threat to cyber security. Malicious URLs host uninvited content like malware, spam, drive by downloads phishing, etc. Users become victims of scams like financial loss, thieving of personal data, malware installation, and causes losses of millions of dollars every year. There is a need to detect those threats in a very efficient and timely manner. Several studies have examined different techniques to handle the problem; the foremost used approach remains blacklisting. The most obstacle to using blacklist is that the difficulties in maintaining an up-todate list of URLs. So here we proposed the Machine learning approach to detect the malicious URLs. We also discussed various methods for malicious URL detection, feature representations, and finally discussed various algorithms for the classification and feature extraction.

Healthcare data analysis is becoming one of the most promising research areas. Diabetes, Liver Disease and Chronic Kidney Disease combinedly affects a mass of world's population. The objective of this briefing is to develop an efficient decision support system to predict the possibility of a disease using the techniques of Machine Learning. Machine Learning is used to discover patterns in the data, detect and analyze trends and then make predictions with the help of algorithms. It provides methods, techniques and tools that can help in solving diagnostic problems in a variety of medical domains e.g. prediction of disease progression, extraction of medical knowledge for outcome research, therapy planning and support, and for the overall patient management. It offers a principled approach for developing sophisticated, automatic, and objective algorithms for biomedical data. This paper mainly focuses on diagnostically predict the possibility of mainly three diseases: Diabetes, LiverDisease and Chronic Kidney Disease.

Through the history, the significant amount of solid waste generated by humans was due to low population density and low levels of the exploitation of natural resources.Common waste produced during pre-modern times was mainly ashes and human biodegradable waste, which were released into the ground locally, with minimal environment impact.Tools made out of metal or woods were generally reused or passed down the generations and generations.However, in mid-19th century, due to cholera outbreaks and the emergence of a public health debate that the first legislation on this solid waste issue emerged.The Sanitary Condition of the Labouring Population in 1842 of the social reformer, Edwin Chadwick, in which he argued for the importance of adequate waste removal and management facilities to improve the health and wellbeing of the city's population was highly effective.Internet of Things (IOT) is playing an important role in many application fields such as home, industry, environment and health.This approach can be applied in the field of solid waste management.In this paper a new cost…

The present study aims to investigate the effect of in-lay material and number of tuck points in wales on the physical, moisture management and thermal comfort properties with plaited double knit fabrics.For this purpose, two types double knit plaited fabric structures such as fabric layer connected with inlay-yarn in all wales line as well as once in every sixth wales line have been developed with same cotton yarn in outer and inner layer.The inlay yarn of cotton and polyester with two different polyester yarns (4.6 dpf&0.54dpf) was used.The result shows that knit structures with different inlay tuck pints, are highly influences the physical, moisture management and thermal transmission properties as distinct from inlay materials.

Advances in ultimate technologies should be begun to the growth of the Internet of Things (IOT). During the new health care situation, the usage of IOT technologies makes the assistance of doctors and patients since they are utilized in various medical sections (such as real-time monitoring, patient data administration, and healthcare supervision). The body sensor network (BSN) technology is one of the central technologies of IOT developments in thehealthcare system, wherever a patient can be observed using a group of small powered and lightweight wireless sensor nodes.Yet, the evolution of this new technology in healthcare applications externally thinking security makes patient privacy unprotected.highlight some essential protection provisions in BSN based modern healthcare system.Consequently, begin a secure IOT based healthcare system using BSN, which can efficiently fulfill those conditions.

Keyloggers are very famous tool which are often used to harvest confidential information.One of the main reasons for this rapid growth of keyloggers is the possibility for programs running in user space to monitor all the keystrokes typed by the users of a system.They are a type of rootkit malware that attempts to retrieve confidential information by covertly capturing user input via keystroke monitoring and then relaying this information to others, often for malicious purposes, it intercepts sensitive information such as usernames, PINs, and passwords.Keyloggers thus pose a major threat to business and personal activities such as Internet transactions, online banking, email, or chat.To deal with such threats, not only must users be made aware of this type of malware, but software practitioners and students must also be educated in the design, implementation, and monitoring of effective defenses against different keylogger attacks.The paper provides an overview of keylogger programs, discusses keylogger design, implementation, and usage, and presents effective approaches to detect…

This study is performed to analyze the use of VGG16 in providing and improving the road extraction from remote sensing images (RSIs). As you can see in the past few years deep CNN is widely used in various applications to detect patterns and to analyze them as well. VGG16 which is also known as oxfordNet is a convolutional neural network (CNN). VGG16 mainly serves the purpose of classification and detection of objects. U-Net is considered as one of the standard CNN architectures for image classification tasks. It is considered as a best network for fast and precise segmentation of images. In this paper, we address the issue of speed and size by proposing a compressed convolutional neural network model namely Residual Squeeze VGG16. Proposed model compresses the earlier very successful VGG16 network and further improves on following aspects: (1) small model size, (2) faster speed, (3) uses residual learning for faster convergence, better generalization, and solves the issue of degradation, (4) matches the recognition accuracy.

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.

To decrease the problem of less living land and the introduction of high rise structures let any country comes under their goal to achieve the sustainability. The Multistoried structures are built and consume a lesser land area that ultimately takes the city into metropolitan one. If any city comes under the huge construction, the investments are also generated that make it as a major city across the country. The buildings taller in height are the only possibility presented since it delivers more correctness in lesser space consumption. In this study, various papers allied to this topic are intensively reviewed in which an enormous work is done in this field earlier. To make these buildings inexpensive, harmless and suitable it is really important to add new ideas and expertise. Among them, stability increment techniques are now demands more in the field of structural engineering. By the help of this study, various papers are reviewed intensively in which a huge work has been done accompanying to this subject. With the help of this literature survey, we came to know the conclusive…

This is the era of Technology; this era belongs to us. The word Internet of Things will be like our new family member soon, it can be implemented in different aspects of our daily lives to make the result accurate and desirable. The term Face Recognition and detection is like an ocean of research and innovation with the applications of image analysis and algorithmbased understanding which can be called as computer vision. Security is a right which no one can deny and justify this right lots of works and researches are taking place in this world. With the development of IoT home security has been developed in recent years with different advancements. We have, Face Recognition as our project. Facial recognition involves the detection and identification of the image. It uses an image capturing technique in the system. The camera catches the facial picture and compares it with the image which is stored in the database. If the picture is matched with the database the gate will open or else a notification will be sent. The recognition algorithms will be from the OpenCV library.

In the cutting edge political atmosphere, counterfeit news is a developing and real risk to our establishments and all voters.Counterfeit news stories are those which are "deliberately and unquestionably bogus".This venture is planned for executing blends of different component extraction systems alongside different Machine Learning calculations from unmistakable classes and to distinguish counterfeit news stories through their substance.The consequences of this regulated parallel content arrangement issue will be looked at and positioned.Kaggle which is claimed by Google LLC and is a network of information researchers and AI engineers which will satisfy our necessity of a dependable source that furnishes us with an evident dataset of genuine and phony news.To reflect this present reality condition, the amount of phony news stories in the dataset, will be considerably not exactly the measure of genuine news stories.An informational collection with around 85: 15 proportion will be utilized.

It influences the nearness and presence of a web webpage inside the principal page of a look motor.The perceivability of a web webpage will be paid or unpaid., yet by and large if a web website needs to search inside the top situation after a natural pursuit then PC program advancement is that the most critical vital instrument to utilize.The full web showcasing procedure hovers round the SEO.The calculation utilized in web search tools.Online nearness of an organization isn't just a direct gratitude to reach among the objective clients however it ought to be beneficial as well if advancement is done keeping noticeable of the objective clients as of the method of reasoning that most of the time clients get your hands on with the watchwords of their utilization as opposed to looking through the association name, and on the off chance that the page connect goes in close vicinity to the top positions, at that point the page is additionally gainful.

Road transport plays a vital role in social, economic and industrial development of the country.Roads are used by different vehicle class which results in failure of the pavement due to early deterioration.The failure of bitumen pavement is due to fatigue cracking and rutting deformation.This paved a way for developing the software like IITPAVE which determines the stress and strains values at critical location at different layer of pavement.This project aims at collection of data related to traffic studies and subgrade soil CBR values from the field and designing the flexible pavement as per the guidelines of IRC: 37-2012.Later it is analyzed using the IITPAVE Software to check whether it satisfies the specific requirements.An international studies have been carried out by World Bank to extend the scope of HDM-3 Model and to provide an organized system approach to the road management with adaptable and user-friendly software tools.This has resulted in development of new set of Highway Development and Management tools referred as HDM-4 Software by incorporating various new features…

Engineers and researchers in the automobile industry have tried to design and build safer automobiles, but traffic accidents are unavoidable.Patterns involved in dangerous crashes could be detected by developing a prediction model that automatically classifies the type of injury severity of various traffic accidents.These behavioral and roadway patterns are useful in the development of traffic safety control policy.It is important that measures be based on scientific and objective surveys of the causes of accidents and severity of injuries.The system presents some models to predict the severity of injury that occurred during traffic accidents using machine-learning approaches.We considered networks trained using learning approaches.Experiment results reveal that among the machine learning paradigms considered various paradigms approaches.

The focus of this paper is to develop a system which will allow user to control connected home appliances remotely using an android app.This project is focused on saving human and electric energy.This system consists an android app and Node Mcu.Home appliances are connected with Node Mcu using relays, which is connected to Wi-Fi.By using this System, user can control connected home appliances from anywhere using internet connection.

In recent years, microservices architecture has emerged to become largely popular in DevOps practices and cloud services.Prime reasons for its meteoric rise are, its modular nature, robustness and scalability.Users today require an interactive, swift, and flexible environment on the platforms they use.These requirements can be satisfied by microservices architecture.A microservices framework consisting of microservices and containers delivers a diverse and distributed application.This architecture handles complex tasks as a collection of smaller services as opposed to the conventional monolithic architecture.In a monolithic architecture, it becomes difficult to manage the structure of code.This is made manageable by adopting microservice architecture.Furthermore, it provides scalability, easy maintenance and independent deployment of services to an application.It enables small parts of an application to be updated, replaced and scaled effortlessly.In this paper, we discuss the architecture of microservices and technology enabling its function.

Blockchain technology is the key for decentralized society and gathered a lot of attention in recent times. The technology of Blockchain offers an infrastructure of secure network that allows the users to perform any operation without middleman. It is expected to bring a revolution due to its characteristics of being transparent, secure and scalable. Blockchain technology will bring the considerable efficiency gains, transparency, cost savings and fraud detection while allowing the data to be shared in real-time between multiple parties in a trusted and transparent manner. This chapter elaborately discusses the basic building blocks of Blockchain technology such as public key cryptography, Digital signature, Elements and types of Blockchain and its applications in different sectors.