The equivalent mixes were obtained by substitution cement by marble dust and fibers partly and absolutely. But economy, technical viability& entrepreneur acceptance are other factors that should be keep in mind while designing the concrete. Hence we also performed cost benefit analysis of concrete while replacing conventional concrete by marble dust and fiber mix concrete and discussing the feasibility of marble dust and fiber mix concrete for entrepreneur also.

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Seismic analysis is one of the most important tasks to understand the behavior of structure under action of earthquake loading. Different system is generated to reduce the effect of earthquake loading. TMD (tuned mass damper) system is one which is used to reduce the vibration of the building. Further with the arrival of response spectrum analysis and time history analysis with better understanding of seismic response. The importance of reduced vibration and displacement of structure is realized in resisting even higher seismic loads than the design load. The design base shear force is reduced by introducing a response reduction factor to consider an inelastic displacement capacity of ductile structure in dissipating the energy of structure.

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In today's modern world there has been enormous development in the field of "Concrete Technology". With this development, there has also been enormous use of concrete in our day today life. Concrete mainly comprises of cement, sand and aggregate as its main constituents, which when mixed with water in correct proportion gives a byproduct called as "Concrete". The excess use of concrete has led to the environmental impact in terms of resources utilization as well as in terms of pollution. To overcome these impacts the concept of "Green Concrete" came into existence. Green concrete is a recent form to the existing types of concrete which resembles the conventional concrete but its manufacturing or handling of this concrete requires minimum amount of heat energy and causes the lowest harm to the surrounding environment. Since it deals into uses of the recycled aggregates and materials, it also reduces the extra load in landfills and mitigates the wastage of aggregates. Thus, the net CO2 emissions are reduced. The reuse of materials also contributes intensively to economy. Green concrete can be considered elemental to sustainable development since it is eco-friendly in nature. One of the methods for manufacturing of green concrete involves reduction of amount of cement in the mix, which added to the reduction the total cement consumption. The use of waste materials also solves the problem of disposing the excessive amount of industrial wastes. Green Concrete is a concrete in which one or more of its constituents are replaced by a resource saving material, which ultimately has reduced environmental impacts in terms of both, resource utilization and pollution impacts together. This paper discusses the importance of Green Concrete in the present day context and highlights its merits over conventional concrete which otherwise posing a serious threat to the environment through global warming.

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In the last few years auto-components industry has experienced healthy growth. The rapidly globalizing world is opening up newer avenues for the transportation industry, especially while it makes a shift towards electronic, electric, and hybrid cars, which are deemed more safe, efficient, and reliable modes of transportation. The fuels that are prevalent throughout the automotive industry, including Electrical components, petrol, solvents, paints, and engine oils, are highly flammable and present the most immediate and obvious fire hazard on these premises. Availability of fire protection systems is not the only solution for fire until they are adequate. Fire load assessment provides information about fire risk and its control measures. In this dissertation, the systematic method has been adopted for the assessment of fire load which will help us to assess the adequacy of an existing fire protection system for automobile systems. This dissertation enables how fire protection system is correlated with the combustible material & its calorific value. Most of the companies have their own fire protection system but they are really adequate, it really needs to be assessed.

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Automobile is the most important mode for the transportation, during this current era. Thanks to the technological advancements there have been heap of recent upgrades, new safety options offered that comforts the motive force and additionally the passengers. Manual engagement of clutch whereas shifting between the gears in traffic areas could be a feverish job for drivers. At some purpose, most drivers can are exposed to a trying scenario behind the wheel, be it a traffic congestion, violence incident or inconsiderate behaviour by alternative drivers. Indeed, a survey conducted by Brake and Direct Line disclosed that seventy one of drivers had lost concentration at the wheel thanks to stress or annoyance. Fatalities and injuries ensuing from road traffic accidents square measure a significant and growing public pathological state in Asian nation. Every week nearly 2,650 people get killed and 9,000 get injured due to traffic accidents by stress. This project is proposed to avoid the necessity of pressing the clutch plates while changing gears. The semi-automatic clutch system comprises a sensor in the gear rod knob. With this sensor the motive force controls the clutching operation. The dominant is completed with a Proportional management Valve and therefore the exploit by a double acting cylinder. The positioning of the clutch is completed by the gas by victimization metering out circuit. Hence engaging of the clutch is completed semi-automatically by this mechanism and therefore the retraction of the gas cylinder is achieved smoothly. Rather than pressing the clutch manually, the engagement and disengagement of the clutch is completed semi mechanically. Driver so are experiencing a lot of comfort in 2 pedal systems than in common 3 pedal systems. This project are a lot of snug for amputees who have the spirit of driving serious vehicles.

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The project emphasizes on design & construction of river cleaning mechanism. The system is successfully able to clean the floating solid waste over the river surface more efficiently. This system works towards its social aim of cleaning the rivers & other water bodies. The conventional & generally used method of cleaning or more precisely collecting the floating waste are manual or by means of boat etc. and are deposited near the shore of river. But these methods are risky, costly, time consuming and required major workforce. By considering all the parameters of water surface cleaning systems and eliminating the drawback of all the methods mention earlier, the water surface cleaning machine has been design and constructed which helps in river surface cleaning effectively, efficiently . The main aim of the project is to reduce the manpower, time consumption and thereby increasing the efficiency of the machine for cleaning the river. In this project, we have the operation of water cleaning with the help of motor, conveyor belt arrangement.

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Landslides or landslip occurs at the down slopes. Landslides are most common in the Asian countries. The movements of rock mass or soil under the gravity are causes due to both Natural and human activities. Increase in the hydrostatic pressure, by saturation of rain water, melting of snow, increase in groundwater level, increase of pore water pressure, volcanic eruptions and earthquakes are natural causes of the landslip. Human activities include the deforestation, cultivation, machinery vibrations, blasting mining etc. Decrease in the shear stress and increase in the shear strain borne by material cause the change in the stability of the slope. Landslide causes extensive loss to the human lives and properties this makes important to monitor and make early warning systems. An attempt is made to create low cost and effective warning system IOT based landslide detection system. Using Arduino, Wi-Fi module, Moisture Sensors and Vibration sensors. When data is collected it is uploaded by Arduino to the cloud ThingSpeak which help to monitor the real time data and send alert to the end user via SMS on the mobile phone about the Landslide when it happens.

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Past earthquakes in India have revealed that majority of the buildings are not designed to be earthquake resistant. Generally, buildings are designed taking into account only the gravity loads. Also, the current design seismic codes are not fully practiced while designing a building. Hence, a higher degree of damage may be expected during an earthquake if the seismic resistance of the building is inadequate. This work is concerned with the effects of various vertical irregularities on the seismic response of a structure. Study of the comparison of the results of analysis of irregular structures with regular structure was done. The scope of the project also includes the evaluation of response of structures subjected to high, low and intermediate frequency content earthquakes using response spectrum analysis. Different types of irregularities namely mass irregularity, stiffness irregularity and vertical geometry irregularity were considered. Tall structures were found to have low natural frequency hence their response was found to be maximum in a low frequency earthquake. It is because low natural frequency of tall structures subjected to low frequency earthquake leads to resonance resulting in larger displacements. If a high rise structure (low natural frequency) is subjected to high frequency ground motion then it results in small displacements. Similarly, if a low rise structure (high natural frequency) is subjected to high frequency ground motion it results in larger displacements whereas small displacements occur when the high rise structure is subjected to low frequency ground motion. The complex shaped buildings are now days getting popular, but they carry a risk of sustaining damages during earthquakes. Therefore, such buildings should be designed properly taking care of their dynamic behaviour.

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The difficulty of taking attendance each and each period by the is extremely time consuming and tiring also Attendance management in any institution may be a very lengthy process and very time consuming. Furthermore, biometrics attendance system is also available but these methods too are time consuming and students have to form a queue for scanning their thumb. The Attendance will be recorded using camera, which will capture images of students and the attendance notification will be sent via E-mail.

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A simplified inverter topology using switching pulse Feed Forward Control Loop (FFCL) for grid integration of photovoltaic (PV) system is proposed. For grid-tied operation of PV-system two topologies are mentioned in literature, namely single-stage (SS) and dual-stage (DS). SS employs only one converter which regulates the DC voltage of PV and also integrates PV with grid. While in DS two converters are used to perform the above mentioned task individually. In this work for a three phase DS-PV system is designed for smooth operation with grid connectivity. Efficiency comparison between conventional Voltage Source Converter (VSC) and proposed inverter topology for PV system configurations is discussed. The system is designed in MATLAB simulink to study its performance for various loading conditions.

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Image data augmentation is a technique that can be used to artificially expand the size of a training dataset by creating modified versions of images in the dataset. Training deep learning neural network models on more data can result in more skillful models, and the augmentation techniques can create variations of the images that can improve the ability of the fit models to generalize what they have learned to new images To increase performance of CNN we can use various types of augmentation methods. In this paper we are discussing about the techniques used to increase the data set size for plant disease detection. Here we take Chili plant diseases as an example and try to increase the collected real time data set size using various augmentation methods.

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In the past few years, generating descriptive sentences by the machine of any image data gained an immense curiosity in computer vision and natural language processing research. Captioning the image is a basic job which requires the understanding of image data and potential to generate descriptive sentence with the correct structure. Image captioning models follow the conventional encoder-decoder architecture which uses the features of the image data as input and generates transcription. Image captioning needs to identify the important entities, their attributes, and their connection in an image data. It is also primely important that the model can make the sentence semantically and systematically. The deep learning-based model is proficient to manage these complications and challenges of image captioning.

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The primary elements of aggregate in concrete are to settle the measurements of the concrete part by decreasing the volumetric changes because of drying shrinkage of the bond water glue in solidified concrete, to diminish the warmth of hydration, and to go about as a filler materials to streamline in the using of concrete. Since aggregate is a noteworthy important piece of concrete, its qualities fundamentally influence the workability of crisp concrete, solidness, strength, warm properties and unit weight of solidified concrete. Concrete is one of the popular construction materials available today. Concrete is Concrete has found use in all types of construction form highway, canal, bridge, and dams to the most beautiful and artistic of buildings. It’s formed by mixing cement, coarse and fine aggregates, water, and additives in a certain prescribed proportion. Aggregate is one of the main ingredients in concrete. It covers more than 60-75% of the overall volume of concrete mix.

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The purpose of this study to measure birth weight of new born babies as well as determining cord blood total antioxidant status and malondialdehyde (product of oxidant injury). Oxidative stress injury has been linked with some clinical conditions in newborn. This cannot be readily measured. Measuring placenta and birth weight along with other features may help in predicting likelihood of oxidative stress injury babies have suffered. Serum extracted from cord blood of subjects was used for the laboratory determination of Antioxidant activity, malondialdehyde and Uric acid. There were positive correlations between birth weight and AOA(r= 0.761,p<.0001), between birth weight and Uric acid(r=0.184;p=0.157). There were significant negative correlations between placenta weight and MDA(r=-0.739; p<.0001)

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Spur gears are an important part of any mechanical engineering component. These are used in applications of power transmissions between two shafts where centre distance between shafts is very less. Gear drives provide higher efficiency that other type of power transmission drives. These are very sensitive in nature too hence a great degree of care must be taken in order to design gears. Current analysis focusses on comparative analysis of spur gears using different kinds of materials other than conventional material of mild steel so that its performance can be improved. In order to conduct the analysis six different materials Aluminium alloy, Gray Cast Iron, Carbon Fibre, E Glass, Epoxy Carbon & Epoxy E Glass have been used. All these materials have been tested on the basis of contact stress being generated. A CAD model of spur gear has been developed in CATIA V5-6 R2017 and Static Structural Analysis has been performed. This data has been compared with numerically solved data. After validation all the materials have been analysed in ANSYS 19.2.

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Globally, fish production in the wild is decreasing and different aquaculture systems are presently used for the development of broodstock in captivity. Broodstock raised in captivity undergoes severe reproductive dysfunction at the level of the brain-pituitary-gonad (BPG) axis. To stimulate growth and maturation of gametes, different techniques like hypophysation and LIPNE based methods targeting BPG axis are used. The paper highlights the problems of reproductive dysfunction in captivity and methods used in induced breeding.

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Water is the basic need for the existence of life on earth. In spite of 70% water on earth majority of water is not suitable for drinking purpose. There is a huge demand of clean water as it is used for a variety of purpose such as drinking, bathing, cleaning, cooking etc. Impurities present in water can cause serious health issues that can damage the life of human beings. The main objective of doing this project is to clean the garbage present in small and big lake. To reduce the cost of river cleaning by use of river surface cleaning 4 machine. To tackle the problems about wastage, food material, plastics present in the lake. To clean the polluted water reservoirs to save the life of aquatic animals. To reduce the human efforts by automation in machine. To make ecofriendly and cost efficient machine without use of liquors like petrol or diesel.

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to detect the presence of Malaria parasites in Human Blood Cells and to determine how much it is affected. We have developed a machine learning method that can detect malaria parasites in thick blood smear images. Our method consists of two processing steps. To start with, we apply a force based Iterative Global Minimum Screening (IGMS), which plays out a quick screening of a thick smear picture to discover parasite up-and-comers. Then, a customized K-Nearest Neighbor (K-NN) classifies each candidate as either parasite or background. Malaria - a parasitic disease health problem which leads to millions of deaths especially in remote villages. This disease arises due to damaging of red blood cells. This paper presents a survey on detection / prediction of malaria disease using various machine learning techniques, Image Processing techniques and various clinical methods like rapid test, Nested PCR etc. In our observation, we found that machine learning techniques have wider applicability for critical diagnosis of malaria which in turn helps the clinicians for diagnosing the disease.

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Today social robots possible to perform roles of elder care, personal familiar, hotel caretaker, and in day-to-day interaction, and with the cost-electiveness of automation, this trend is now popular. However, one of the problem of introducing robots to new domains is the creation of social interaction logic, which principle how the robot behaves and interacts with people. It is tedious for an interaction designer to create all the behaviors for a robot by hand, and it is an incredibly challenging task to expect all the varieties of ways that humans may behave in a social interaction. To solve the problem of responding to human actions, a fuzzywuzzy logic [fig 5] algorithm with pandas data frame can be used. The system trained human-readable rules that prescribe which action the robot should take, based on taking input from designer(conversation data take from csv table [table 4] && [table 5]). In this system the above technique is can be applied to the robot learns to play the role of a travel agent.

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The aim of this paper is to give an innovative concept to handle energy demand around the world is increasing rapidly for many applications. Renewable sources of energy are solar, wind and geothermal which are inexhaustible. Solar energy is abundant in nature and is proving its existence for many applications like street lighting, house hold appliances, water heating, agricultural and industrial purpose. One of the way to harness solar energy is done by using solar panels. Limitation of solar energy is its efficiency for any application due to the factors like dust, humidity, temperature etc. Electrical parameters of solar panel are sensitive to accumulated dust density and will affect the transmittance of the solar panel thereby reduce its efficiency. In order to overcome this problem, it is necessary to clean the solar panels regularly. One of the method is to increase the efficiency of solar panel is by removing the dust accumulated on solar panel. Cleaning of solar panels is difficult task. The normal way to clean the solar panels is washing them manually but it is not reliable and economical. In this regard a work is taken up to design and implement the automatic dust cleaning mechanism for solar panel. The designed automatic cleaning mechanism consists of IR LED, Photo diode arrangement in order to sense the dust accumulated on solar panel. The efficiency of solar panel is determined by taking the readings of voltage and current of particular panel with and without dust for various days, weeks and months. By the recorded values efficiency comparison of solar panel with dust and without dust is made. The designed automatic cleaning system produces an effective, non-abrasive cleaning and avoids irregularities in the generation of power due to the deposition of dust on the solar panel. From the study it is proved that average efficiency of solar panel increases about 1.6% to 2.2% by regular cleaning. Thus developed model maximizes the efficiency.

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It is vital that credit card companies are able to identify fraudulent credit card transactions so that customers are not charged for items that they did not purchase. Such problems can be tackled along with Machine Learning. This project intends to illustrate the modelling of a data set using machine learning with Credit Card Fraud Detection. The Credit Card Fraud Detection Problem includes modelling past credit card transactions with the data of the ones that turned out to be fraud. This model is then used to recognize whether a new transaction is fraudulent or not. Our objective here is to detect 100% of the fraudulent transactions while minimizing the incorrect fraud classifications. Credit Card Fraud Detection is a typical sample of classification. In this process, we have focused on analysing and pre-processing data sets as well as the deployment of multiple anomaly detection algorithms such as Naïve bayes, K-Nearest Neighbours, Logistic Regression and Support Vector Machine Model. Due to a rapid advancement in the electronic commerce technology, the use of credit cards has dramatically increased. Since credit card is the most popular mode of payment, the number of fraud cases associated with it is also rising. In this paper, the survey on the present techniques available for detecting fraud in credit card is presented as a review paper. Fraud detection involves identifying fraud as quickly as possible once it has been done. Fraud detection methods are continuously developed to defend criminals in adapting to their strategies. The transaction is classified as normal, abnormal or suspicious depending on this initial belief. Once a transaction is found to be suspicious, belief is further strengthened or weakened according to its similarity with fraudulent or genuine transaction history using Bayesian learning. This paper investigates and checks the performance of Decision tree, Random Forest, SVM and logistic regression on highly skewed credit card fraud data. Dataset of credit card transactions is sourced from European cardholders containing 284,786 transactions. These techniques are applied on the raw and pre-processed data. The performance of the techniques is evaluated based on accuracy, sensitivity, specificity, precision. The results indicate about the optimal accuracy for logistic regression, decision tree, Random Forest and SVM classifiers are 97.7%, 95.5% and 98.6%, 97.5% respectively.

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The energy consumption can be monitored by using of electrical device is known as energy meter. In this we had made some changes and modifications adding in addition of voltage and current sensor in order to monitor respected term value for different use like V, am, Unit, etc, Thus the monitor data is sent to cloud for later use for bill etc. And used to avoid error occurred during bill calculation.

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Durability plays major role for any concrete structure. Durability is ability to resist different weathering conditions. Chloride ion permeability in concrete will effect on durability. Durable concrete will retain its original form, quality and serviceability when exposed to environment. In this present work, we have done tests on cement, fine aggregate and coarse aggregate. We have done the mix design as per IS code 10262-2009 for concrete of grade M30. We conducted compressive strength test and rapid chloride ion permeability test on concrete of grade M30 by using different cements like Ordinary Portland Cement, Portland Pozzolana Cement& Portland Slag Cement. We conducted the RCPT to determine the penetration of chloride ions for different ages of concrete like 28days & 60days. From the results, finally we concluded that Portland Slag cement has highest resistance against chloride ion penetration.

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Sentiment analysis (also known as opinion mining) is process of extracting information from user's opinions. Every person shares his or her information on social network sites, blogs, product review websites and web-forums. Thus, we get familiar with the thinking of the other people. People's thinking that provides an information that helps in decision making process. This Paper describe different applications of sentiment analysis, techniques and challenges of sentiment analysis. This survey would cover various approaches and methodology used in Sentiment Analysis and Opinion Mining in general. The focus would be on Internet text like, Product review, tweets and other social media.

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We present our implementation of using a motion controller to control the motion of a drone via simple human hand gestures. This can be achieved by building a transmitter and receiver, different from traditional ones, which can be used to easily control a drone. For the implementation of the motion controller, we have used a 2.4GHz Tran receiver and an Arduino Uno. The basic problem with the traditional transmitters/controllers use a multitude of switches, levers, and joysticks to control a drone. The Trans receiver recognizes the hand gestures and relays them onto the ground station. In our implementation, we have written Arduino programming codes to interpret the hand gestures captured by the Trans receiver, and transmit them to control the motion of the drone via these gestures the same gyroscopic glove in the prototype project will be used to control the drone. The BT module is swapped out for a 2.4 GHz Tran receiver for better range, lower latency, and higher bandwidth. The glove sends out a PPM signal to the receiver connected to the drone. The signal consists of values derived from the MPU6050 Gyroscope, which is then converted to a type recognized by the drone, which in this case being the PPM Signal. The Drone is fitted with a flight controller. A Drone Flight Controller (FC), is the heart of a quadcopter and controls most onboard electrical components with the assistance of an Arduino-like microprocessor and an array of sensors. The FC is outfitted with a gyroscope and an accelerometer to calculate its angular velocity and speed and make the optimum calculations required to keep the drone flying. The FC is mounted on the drone and is connected to 4 equally spaced out coreless DC motors responsible for the flight. The Drone is also outfitted with the same 2.4 GHz receiver that receives input from our gyroscopic glove and sends it to the flight controller, which uses that data for its flight. According to the tilt and the acceleration of the glove, the Trans receiver sends appropriate data to the drone for it to change it is at altitude or tilt and move around

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