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Predicting Heart Attack
Heart diseases are increasing day by day, and predicting these diseases is very important and worrying. This diagnosis is a difficult task because it must be done accurately and efficiently. Most studies focus on patients at risk for heart disease based on a variety of medical conditions. We proposed a heart disease predictor that uses the patient's medical history to predict whether a patient will be diagnosed with heart disease. We use various machine learning algorithms, such as logistic regression and KNN, to predict and classify heart patients. A useful way to formalize how the model can be used to improve the accuracy of heart attack prediction for each individual The power of the model is very good and can predict the evidence of heart disease in an individual using KNN and logistic regression, comparing performance with other methods and previously used classifiers such as Naive Bayes. By using the given model to find the probability of the distributor being correct and to determine the heart disease, we have taken most of the pressure off ourselves. Predicting heart disease improves health and reduces costs. This project has given us important information that can help us predict patients with heart disease
Experimental Study on Green Concrete using Graphene
The paper considers methods for concrete modification using low-layer graphene and grapheme oxide. It was found that graphene oxide and low-layer graphene obtained by liquid-phase shear exfoliation significantly increase the strength of concrete. In our opinion, low-layer graphene has better prospects since it is cheaper and its production technology is environmentally friendly. The viability and future of graphene largely depends on the availability of such a method that allows mass production of high-quality graphene at an affordable price. In this regard, liquid- phase separation of graphite with the formation of low-layer graphene, which can be used to modify concrete, turned out to be a competitive solution. The following main tasks were formulated in order to solve the organizational problems of low- layer grapheme industrial production: reducing the concentration of low-layer grapheme in concrete; increasing the concentration of low-layer graphene in suspension; developing an industrial technology for the production of concentrate with a high content of low- layer graphene; conducting full-scale experimental studies to determine the optimal concentration of low-layer graphene in concrete.
Online Diagnostic Lab Reporting System
The project “ONLINE DIAGNOSTIC LAB REPORTING SYSTEM” is to develop web application to computerize the Management of a Diagnostic System which is user friendly simple, fast, and cost-effective. It deals with the collection of patient’s information, diagnosis details, etc. Traditionally, it was done manually. The main function of the system is register and store patient details and staff details and retrieve these details as and when required, and also to manipulate these details meaningfully. System input contains patient details, diagnosis details, while system output is to get these details on to the screen. The Online Diagnostic Lab Reporting System can be entered using a username and password. It is accessible by every level of user according to their role. Every user can view the data that they are accessible. Only that user can add data into the database who has editing permission. The data can be retrieved easily. The data are well protected for personal use and makes the data processing very fast.
Experimental Behaviour of Concrete by Partial Replacement offline Aggregate Using Iron Powder
One of the main goals of the sustainable solid waste management is to maximize the ability of its recycling and reusing. Iron waste and steel are the most common of these materials. With increasing environment pressure to reduce waste pollution, the concrete industry has been adopting a number of methods to achieve these goals. Preserving natural aggregate is a matter of sustainable development to ensure sufficient resources for future generation. Reuse of iron powder waste as partial replacement of fine aggregate in construction activities results in reducing the demand for extraction of natural raw materials. The quality of aggregate is highly important since approximately three-quarters of concrete volume are occupied by aggregate which are greatly affects the strength, durability and the structural performance of concrete. Must research effort has focused on reusing waste material from iron and steel industries to partially replace the aggregate in concrete mixes.
Experimental Study on Steel Fibre Reinforced Rubberised GGBS Based Geopolymer Concrete
Geopolymer concrete is a sustainable material which can reuse industrial by-products and thereby minimize the emission of greenhouse gases during its production, unlike cement. This geopolymer concrete is found to develop high strength within a short period of ambient curing. It is observed that the addition of steel fibers enhances the strength and durability characteristics of this concrete. The paper highlights the engineering and durability properties of steel fiber-reinforced GGBS-dolomite geopolymer concrete and explains how the bond strength and impact resistance of GGBS-dolomite geopolymer concrete is improved by the inclusion of steel fibers.
Predicting Fuel Efficiency of Vehicles using Machine Learning Algorithms
we have planned to create a model to predict fuel efficiency of various kinds of vehicles through several stages. This model includes metaphors of various different cars from different periods. This metaphors consists of the following things such as cylinders, displacement, horse power, and weight .we have taken a datasets related to this work from kaggle .The machine learning algorithm is appropriate one for this type of analysis to learn patterns and design models from them for predicting fuel efficiency Decision Tree, Random Forest, linear regression,K-nearest neighbor used to produce less error with improved efficiency and the algorithm are compared
Experimental Investigation on Strengthening of Geo-Polymer Concrete Slab with Bubble Technology
The bubble deck technology developed in Europe makes use of high-viscosity concave polyethene spheres to replace the ineffective concrete in the centre of the slab, therefore dwindling the dead weight and adding the effects of the bottom. This system is used in the concrete floor system. Concrete is good in contraction and hence is more useful in the contraction region than in the pressure region. The reduction in concrete can be done by replacing the pressure zone concrete. An experiment has been carried out to find out the effectiveness of plastic bubbles by replacing concrete in the pressure zone of Ordinary Portland Cement Concrete (OPCC) and Geo-Polymer Concrete (GPC) slab. Constituents named are cement, sand, and coarse aggregate for OPCC and for GPC cement is fully replaced with 70% fly ash, 15% GGBS and 15% glass powder. NaOH(12M) alkaline solution is added instead of water for GPC. In this design, M45 concrete blend is used to prepare both OPCC and GPC slabs. The trial blend is tested for compressive strength in 7 days and 28 days. A flexure test is done for 7 days and 28 days of curing of the beams. The procedure is repeated for beam samples with bubble mesh and bubble mesh along with shear underpinning. Relative analysis of the OPCC and GPC slabs is done to observe the chance reduction in tone-weight and cost-effectiveness. Analysis of the geste of the GPC beam in comparison with that of the OPCC beam is also carried out.
Driver Recognition and Drowsiness Detection using Deep Learning Technique
Drowsiness and fatigue of automobile drivers reduce the drivers’ abilities of car manage, herbal reflex, recognition and notion. Such diminished vigilance stage of drivers is found at night time driving or overdriving, causing twist of fate and pose extreme danger to mankind and society. Therefore, it is very tons essential in this recent fashion in vehicle industry to include driving force help system which could hit upon drowsiness and fatigue of the drivers. This undertaking offers a nonintrusive prototype computer vision gadget for monitoring a driving force’s vigilance in real time. Eye tracking is one of the key technologies for destiny motive force help systems for the reason that human eyes contain lots statistics approximately the driver’s condition which includes gaze, attention stage, and fatigue degree. One problem commonplace too many eyes monitoring strategies proposed to this point is their sensitivity to lighting fixtures situation exchange. This has a tendency to seriously restrict their scope for car packages. Real- time detection and monitoring of the attention is an energetic region of research in laptop imaginative and prescient community. Localization and monitoring of the attention can be beneficial in face alignment. This challenge describes actual time eye detection and tracking approach that works underneath variable and sensible lighting fixtures situations. It is primarily based on a hardware device for the real-time acquisition of a driving force’s snap shots the use of digital camera and the software program implementation for monitoring eye that can avoid the accidents.
Seismic Behavior of Reinforced Concrete Bridge and Control Measures for Seismic Pounding
India has had a variety of the world’s greatest earthquakes within the last century. In fact, quite one half area within the country is taken into account vulnerable to damaging earthquakes. The seismic building design code in India (IS 1893, Part-I) is additionally revised in 2002. The magnitudes of the look seismic forces are considerably enhanced generally, and also the seismic zonation of some regions has also been upgraded. There are many literature (e.g., IITM-SERC Manual, 2005) available that presents step-by- step procedures to gauge multi-storeyed buildings. The attention for existing bridges is relatively less. However, bridges are important components of transportation network in any country. The bridge design codes, in India, don’t have any seismic design provision at this time. A outsized number of bridges are designed and constructed without considering seismic forces. Therefore, it is important to gauge the capacity of existing bridges against seismic force demand. There are presently no comprehensive guidelines to help the practicing structural engineer to gauge existing bridges and suggest design and retrofit schemes. So as handle this this problem, this work aims to hold out a seismic evaluation case study for an existing RC bridge using nonlinear static (pushover) analysis. Nonlinear static (pushover) analysis as per FEMA 356 isn’t compatible for bridge structures. So, within the present study an improved pushover analysis is additionally won’t to verify the results.
AI Based Spam Detection Using Logistic Regression Algorithm
Nowadays, a big part of people caused by unsolicited bulk email messages commonly referred to as Spam. Email has now become one of the best ways for advertisements due to which spam emails are generated. Spam emails are rely on available email or messages sent by the stranger. The possibility that anybody can leave an email or a message provides a golden opportunity for spammers to write spam message about our different interests. Spam fills inbox with number of ridiculous emails. Degrades our internet speed to a great extent .Steals useful information like our details on our contact list. Identifying these spammers and also the spam content can be a hot topic of research and laborious tasks. Email spam is an operation to send messages in bulk by mail .Since the expense of the spam is borne mostly by the recipient, it is effectively postage due advertising. Spam email is a kind of commercial advertising which is economically viable because email could be a very cost effective medium for sender .With this proposed model the specified message can be stated as spam or not using Bayes’ theorem and Naive Bayes’ Classifier and Also IP addresses of the sender are often detected.
Experimental Study on Structural Behavior of Self Healing Concrete
The Cracking of concrete is a common phenomenon without immediate and proper treatment, cracks in concrete structures tends to expand further and eventually require costly repairs. Even though it is possible to reduce the extent of cracking by available modern technology, remediation of cracks in concrete has been the subject of research for many years. Cracks and fissures are a common problem in building structures, pavements, and historic monuments. Cement mortar durability is the function of its internal pore structure and distribution, porosity, and its permeation properties. Research has shown that some specific bacterial species isolated from soil can tolerate harsh and challenging alkaline environment and can be used in remediating cracks in cement mortar structures. This state-of-the-art microbial based crack healing mechanism is one such phenomenon on which studies were carried out to investigate the role of calcite mineral precipitation in improvement of durability in bacteria integrated cement mortar. The primary goal of this study is to explore the potential of biomineralization microbial calcium carbonate deposition in cement mortar, to develop sustainable construction materials. The idea has led to the conception of energy efficient and sustainable construction material called ‘Bacterial Cement mortar’. This paper primarily focuses on the studies related to the characterization of bacteria produced calcium carbonate crystals using various nano characterization techniques such as Scanning Electron Microscope (SEM), X-ray diffraction (XRD), and Thermo gravimetric analysis (TGA) to validate that cracks/pore were sealed up by calcite crystals grown due to complex metabolic mechanism of nitrogen cycle by Bacillus subtilis JC3. In concrete, cracking is a common phenomenon developed due to relatively low tensile strength. High tensile strength may be developed in concrete due to external loads, imposed deformations, plastic shrinkage, plastic settlement and expensive reaction. Proper and immediate treatment should be done to prevent expansion of cracks which may eventually be of higher cost. For crack repair, a variety of traditional repair systems are available which possess several disadvantages aspect such as different thermal expansion coefficient, environmental and hazards of health. Bacterially induced calcium carbonate precipitation has been proposed as an alternative and environmentally friendly crack repair technique. It is found that microbial mineral precipitation as a result from metabolic activities of favorable bacteria in concrete improved the overall behavior of concrete. It is expected that further development of this technique will result in a more durable, sustainable, and crack free concrete that can be used efficiently for construction in wet atmosphere where corrosion of reinforcement affects the durability, permeability, and strength of concrete.
Watermarking and Encryption Technique to Avoid Data Leakage in Cloud Storage with Block Chain Technology
Multimedia data sharing is increasingly becoming an essential part of the daily life for end users to access different systems, services, and applications. Data disclosure frequently occurs in real-world cloud storage services. Authentication and copyright protection of multimedia contents has always been a concern in secure data transfer media. The problem has become more critical with the increasing use of the Internet and digital technologies. However, making the protection of copyright is more complex and difficult. In proposed approach both Watermarking and Proxy Re-encryption (PRE) approach utilized for efficient multimedia content sharing. Watermarking is used to hiding the information such as hide secret information in digital media like images. Encryption techniques used to provide security to data. In proposed work, secret key can be encrypted using encryption algorithm with the help of key. Then user’s private key combined with encrypted key information and can be embedded within the image or audio using LSB (Least Significant Bit). After embedding of secret information, image or audio can be encrypting using ECC Encryption algorithm. Finally, authorized user can extract decryption key with the help of embedded data verification process. Unauthorized or illegal access can identify, when user information does not match with embedded information. And also secure these transaction details using Block chain technology.
Current Stock Monitoring System with Expiry Alerts
The main objective of this project is manage a stock for a Developing a “CURRENT STOCK MONITORING SYSTEM WITH EXPIRY ALERTS” is illustrates the designing and implementation of a Current Stock Monitoring Management System with expiry alert system. The primary aim of is to improve accuracy and enhance safety and efficiency in the pharmaceutical store. Today management is one of the most essential features of all form. The Management provides sophistication toper form any kind of task in a particular form. This is pharmacy management system; it is used to manage most pharmacy related activities in the pharmacy. computerized system designed for user to manage the stock inventory and monitoring the stock facility. The stand alone stock inventory system provides alert of expire date and minimum quantity of each product and also searching algorithm technique applied in this system. Are search and analysis on the current system and searching technique was done to get better understanding of the system. The RAD methodology was used in this project development implements iterative development which is suitable for standalone applications requirements that changes from time to time. Testing is done every phase of the development life cycle to make sure that the system working properly.
Agriculture Plants Disease Detection and Preventive Measures
Agriculture serves as a source of energy and a solution to the problem of global warming, in addition to feeding an ever-increasing population. Plant diseases are particularly important because they can have a negative impact on the quality and quantity of crops grown in agriculture. Plant disease identification is critical early on in order to cure and control the illness. The naked eye approach is commonly used to diagnose illnesses. Experts with the ability to identify changes in leaf color are involved in this procedure. This procedure involves a great deal of labor, takes a long time, and is impractical for vast fields. Often, multiple professionals would diagnose the same ailment as a different one. This technology is costly since it necessitates expert monitoring on a continuous basis. Plant diseases can raise the cost of agricultural production and, if not treated early enough, can lead to a producer's utter financial ruin. Producers must monitor their crops and recognize early symptoms of a plant disease in order to limit the spread of the illness at a cheap cost and save the majority of the crop. Hiring expert agriculturists may be prohibitively expensive, particularly in remote and isolated geographic areas. A deep learning algorithm in an image can provide an alternate solution for plant monitoring, and such an approach can be controlled by a professional to provide lower-cost services. It contains features extraction and classification, as well as an image classification strategy that uses a neural network algorithm to forecast various diseases in corn leaf. Also, based on severity analysis and data, extend the approach to prescribe fertilizers.
A Study on Process Management in Supply chain Industry Jailakshmi Group of Company Auto works & Agencies Pvt Ltd., Salem
Quality of work life (QWL) is viewed as an alternative to the controlled approach of managing people. The QWL approach considers people as an ‘asset’ to the organization rather than as ‘costs’. It believes that people perform better when they are allowed to participate in managing their work and make decisions. This approach motivates people by satisfying not only their economic needs but also their social and psychological ones. To satisfy the new generation workforce organizations need to concentrate on job designs and organization of work; further today’s work force is realizing the importance of relationships and is trying to strike a balance between career and personal lives.
Design of Power Weeder Machine
Improper weed control methods can cause about 30–35% reduction in crop yield. Mechanical weed control on ridges is still a major problem. A ridge profile power weeder was designed and developed for weeding of ridge planted crops. The main working components of the weeder were cutting blades and rotor shaft. Three types of blades (L-type, C-type and Flat-type) were selected having length, width and thickness of 100 mm, 25 mm and 6 mm, respectively, operating with a rotor shaft of 18 mm in diameter. C-type blades were most suitable at gang speed of 200 rpm and 15.26±0.96% (d.b) soil moisture content with weeding efficiency, plant damage, field capacity of 91.37%, 2.66%, and 0.086 ha.h-1, respectively. Time saving with ridge profile power weeder as compared to manual weeding was 92.97 per cent.
Karoke Audio Exarction Using Matlab
To isolate sound sources in an audio scene is called audio source separation. Singing voice extraction is one use for source separation. Using the 2D Fourier Transform (2DFT), we provide a unique method for music/voice separation in this study. Our method takes use of the way periodic patterns appear in the 2D Fourier Transform and is related to studies on biological auditory systems and picture processing. We discover that our technique is relatively easy to describe, put into practice, and is competitive with existing unsupervised source separation methods that make use of related presumptions.
IoT Based Blockchains and IPFS
Block chain, the underlying technology of crypto currency networks like Bitcoin, is designed to realize the vision of a decentralized, secure and open Internet of Things (IoT) revolution with a centralized data access model. Essential. It may be so. This article proposes a distributed access model for IoT data using a network architecture called the IoT and Blockchain Modular Consortium Architecture. The proposed architecture facilitates IoT communication via a blockchain software stack and a peer-to-peer data storage mechanism. This architecture is intended to provide privacy and be adaptable to various IoT use cases. To implement the proposed architecture, we conduct a performance analysis of existing blockchain development platforms, Ethereum and Monax.
Constructing Private Cloud Storage using Network Attached Storage
Today, humans live in the "era of the cloud," where you can store numerous resources for later use and exploitation. However, there is a security concern with uploading private or confidential data to a public cloud. Additionally, building a typical cloud storage system would be expensive and requires extensive hardware administration, making it unaffordable for individuals, SOHOs, and small businesses. To establish their own cloud, they require an affordable but reliable option. Therefore less-expensive, adaptable, and recoverable private cloud storage system utilising NAS is suggested in this work. Migration and cell recovery, two key methods for improving adaptability and recoverability, are described, and assessed.
PIEZO- AIDED FOOTSTEP POWER GENERATOR
Just think how much an average person would walk, a person of 80 would have walked 216,262,500 steps throughout life. Then think of billions of peoples. Also think if energy produced is sufficient and reachable to entire mankind. what if you convert this foot step into a useful source rather than wasting it? It would be non-conventional energy for performing work or just light up the street. It would meet the small need for energy for the growing population. This energy of footstep can be used with help of footstep power generator [by using piezoelectric sensors