Movie recommendation is a computer program that recommends movies to users based on their interests and behavioral histories. It uses algorithms to analyze user data such as view histories, ratings, and demographics and matches them with videos that match their interests. The system can also provide integrated filtering, content-based filtering and other methods to provide personalized recommendations. Overall, the purpose of video recommendations is to improve the user experience by making it easier for users to find new videos they like.

Read More...

This paper presents an innovative Online Appointment Booking System for CNG Pump, aimed at reducing waiting times and improving the efficiency of CNG refueling processes. The system allows users to book appointments for CNG refueling through a web- based application, providing convenience and time savings. Utilizing technologies such as GPS and real-time data, users can locate nearby CNG pumps, view availability, book appointments, make online payments, and receive notifications. The system also includes an administrative panel for pump owners to manage pump details, update CNG prices, and monitor appointments. The proposed system enhances the overall CNG refueling experience by streamlining the booking process and minimizing waiting times.

Read More...

Social distancing has become essential to prevent the spread of infectious diseases, especially in crowded areas. This paper proposes a real-time social distancing detection system using deep learning, specifically YOLOv3 (You Only Look Once version 3) object detection algorithm. The proposed system uses surveillance cameras to capture real-time video feeds of crowded areas, which are then processed by YOLOv3 to detect individuals and calculate their distances from each other. The system employs a custom object detection model trained on a large dataset of annotated images and a novel distance measurement method, which takes into account the variations in camera perspectives and distances of individuals from the camera. The experimental results demonstrate its high accuracy and real-time performance. The proposed system can contribute to the development of smart cities and public health systems that helps researchers and practitioners to design and implement real-time social distancing monitoring systems for various applications.

Read More...

Renewable energy is a type of energy, that is derived from ongoing natural processes and energy of natural processes converted into available forms. Solar energy is any type of energy that is generated by the sun. To make use of this energy and convert it into electricity we use solar panels. The IoT allows objects to be sensed or controlled remotely over existing network infrastructure, creating opportunities for pure integration of the physical world into computer-based systems, and resulting in improved efficiency, accuracy and economic benefit in addition to reduced human intervention. This technology has many applications like Solar cities, Smart villages, Micro grids and Solar Street lights and so on. As Renewable energy grew at a rate faster than any other time in history during this period. The proposed system refers to the online display of the power usage of solar energy as a renewable energy. This monitoring is done through atmega328p using ATMEGA328P IDE. Smart Monitoring displays voltages of renewable energy. This helps the user to analysis of energy generation. Analysis impacts on the renewable energy usage and electricity issues.

Read More...

To minimize the cost of earthmoving equipment by optimize the time and cost of earthmoving activities. This was developed to optimize various decision-making variables (i.e., capacity, number, and speed). The optimization results emphasize the ability in creating a wide variety of optimal solutions to minimize time and cost objective functions during earthmoving activities for a wide range of possible equipment combinations. Earthmoving activity is considered one of the most critical elements in construction projects. The overall cost of earthmoving activity during construction projects can account for more Than 30% of the total cost. Moreover, earthmoving equipment emits enormous carbon, which has adverse environmental effects. A mathematical model is needed to optimize the selection of the equipment types (i.e., Dumper and excavators) and the numbers of each type to be employed on a particular project, based on the work capacity of each unit, the number of units, and the speed at which each unit travels.

Read More...

Flat slab construction is a widely used technique in the construction industry due to its versatility, speed of construction, and ability to accommodate flexible column grids. However, this construction technique can lead to large bending moments and shear forces near the columns, which can result in cracks in the concrete and even failure of the slab. To address these issues, the paper proposes the use of column heads, which provide a larger area at the top of the column to distribute the stresses more evenly and reduce the risk of failure. The paper also reviews the design methods for flat slab structures based on Indian and American standards, which provide guidelines and recommendations for the design and construction of safe and efficient flat slab structures. Overall, the paper appears to provide valuable insights into the use of flat slab construction in India and the design methods for such structures based on established standards.

Read More...

In this work, we suggest creating a chatbot assistant for colleges using speech recognition and richer human-computer interaction. By the application of cutting-edge voice recognition and natural language processing methods, the suggested system seeks to improve user experience. College students' regular academic activities, such as locating information about courses, instructors, timetables, assignments, grades, and other pertinent questions, will be made easier by the chatbot. In order to give consumers accurate and pertinent replies, the system will be developed utilizing cutting-edge technology such as deep learning algorithms, natural language processing, and machine learning approaches.

Read More...

Currently, disease detection is important for better crop yield and quality. Deterioration in the quality of agricultural products, plant diseases can lead to huge economic losses for individual farmers. Plants are the food source of the earth. Plant diseases therefore pose a great threat that can cause many infections, while the usual diagnosis is mainly made by examining the plant body for the presence of visual symptoms. In this research, we proposed a deep convolutional neural network to detect plant diseases from leaf images. To detect a disease, we have a dataset that consists of different open datasets and contains images of different plants. All of the steps required to implement this disease detection are fully described in the paper, starting with collecting images to create a database for the data. With the help of this research work, we can find out the disease and reduce the economic losses. Methods based on machine learning can be used to identify diseases since they are mainly applied to data superiority results for specific tasks. In this approach, a comprehensive review of the different techniques used in plant disease detection using artificial intelligence (AI) based machine learning and deep learning techniques was conducted.

Read More...

Reviews on different platforms such as E-Commerce platforms, App Stores, or Online Services are useful for the users as well as the vendors. Reviews help the users in making decisions about buying or using the online service. Similarly, these reviews help the vendors to increase their reputation for the product or service they are providing among the users. But unfortunately, this mechanics of review is misused several times. Both parties try to create fake reviews, to raise popularity or to discredit the product. This research aims to identify fake reviews for a product with the help of text and rating property from a review. In short, we make use of advanced supervised machine learning techniques, natural language processing techniques, and sentiment and opinion mining techniques to identify fake reviews. Using these techniques we identify the truthfulness of a given review by giving good training to the model and using quality training and testing data. The result from this experiment shows that the proposed solution has better accuracy than the previous work.

Read More...

Nowadays, all manufacturers around the world are trying to achieve efficiency as high as possible that being driven by global competition and the fast changing of market demand and needs. Efficiency becomes one of the most critical factors in order to reduce resources usage such as labors, materials, and machines which all leading to cost reduction and productivity increases. Lean manufacturing is a common methodology widely used by manufacturers around the world. The keys in order to apply lean manufacturing are efficiency and continuous improvement. Efficiency can be achieved towards the utilization of technology between shop floor and supporting business layers occurs in a system. While achieving the increased efficiency and productivity maintaining quality standards is very important. In this project we are designing a concept oriented modal of conveyor belt based production line. This line will be fully metal fabricated and sensor integrated. The line will carry the material and process as per the cycle time requirements with sensing of the parts dimensions, rejections and sorting them for avoiding the quality issues. Counter will be implemented at starting and ending of the line, this will help to monitor the use of raw material and exit of the finished goods so that all wastages and rejections can be overall monitored and kept under the control by wiser super and production managers. All this actions will be kept monitored and stored for future analysis onto the IOT Server of the production line. This will benefit the system in terms of analyzing the system performance efficiency and keys to improve the system if needed.

Read More...

In many educational institutes hostels accommodate hundreds of students, so it is essential to design a system for managing various activities efficiently. Attendance Based Hostel Management System is a web application designed for managing activities such as taking attendance, generating the students reports, sending the timely alerts, room allotment to the students and other users. This project deals with problems which occurs due to some manual tasks like generating student attendance reports manually, contacting with the parents of students whenever necessary. Traditional hostel management system was too complex to maintain the record and attendance. Availability of data at specific required time was difficult. Also, to keep the track and watch on hostel activities for higher authority was difficult. In traditional hostel management system, all the things were done by using paper pen, which was time consuming. Also, there was possibility of error. We have taken the drawbacks of the existing system into consideration such as manual entry of record, room allotment, daily attendance and report generation, informing the parents as well as higher authority about absent students to keep the track as well as higher authority can keep the track of attendance of students and there information too. We designed the new system which is compatible to the existing system. The proposed system will help to carry out this manual tasks more efficiently and genuinely with any error and delay.

Read More...

Design a model for a solar parabolic parabolic model for rural areas with high solar irradiance, where there is no electricity, or where low-income people can buy stoves (electricity or gas). The Solar Parabolic Parabolic Prototype aims to provide a solution to such repairs and uses solar energy to work. A paraboloid has a polished surface where solar radiation falls into a concentrated focus. At this point, electronic devices are used to provide different thermal applications; cooking and heating using single and double solutions. The project explores the main phases of the dual pivot model; application, solar field research, theory, basic layout and information.

Read More...

Shock absorbers are crucial parts of cars that provide comfort and safety when driving. The performance traits of shock absorbers under actual use conditions are studied in this essay. Through computer modelling, testing, and experimental analysis, the dynamic behaviour of shock absorbers was investigated. MATLAB was used to validate the findings. Speed brakes were applied to a rotating drum in the model to imitate road disturbances. The research also examines and illustrates the dynamic characteristics curve of a single degree of freedom spring-mass-damper system (Hero Splendour rear shock absorber) for various spring stiffness values and various lubricants.

Read More...

Fiber reinforced soils have become one of the construction materials in civil engineering. Construction of building and other civil engineering structures on availability clayey soil is highly risky, on geotechnical grounds due to poor strength properties of the clayey soil. There may be the need for soil treatment to improve the engineering properties of soil. The purpose of this investigation is to identify and quantify the influence of coir fiber on performance of fiber reinforced soil specimens. In this study, coir fiber mixed with clayey soil in various proportions (0%, 0.5%, 1.0% and 1.5% by weight of dry clayey soil) to investigate the relative strength gained in terms of compaction CBR & Unconfined Compressive strength. The results clearly indicate that 1.5% coir fiber when unsoaked have noticeable influence on CBR value of expansive soil it improved from 1.03 to 2.04. As well as the CBR values after curing for 28 days also showed an increase by 15% after soaking. The unconfined compressive strength was improved by 60% at 1% coir fiber. The UCS also showed an increase about 23% after curing for 28 days. This is because of composite effect of waste materials, which changes the brittle behavior of soil to ductile behavior. So from this study we can state that coir fiber is a good material to enhance the soil properties.

Read More...

The purpose of the study is to determine whether the hybrid work paradigm can be enhanced to promote virtual employees' success in the IT industry. The investigation was carried out with proper consideration of a particular theoretical foundation. While keeping the advantages of remote employment, the hybrid work model approach gives employees more flexibility and a better work-life balance. Data has been verified using analytical techniques, and it has been discovered that working digitally in a hybrid work style is becoming more and more popular. In this study, a sample of virtual workers (N=168) responded to an online survey that included a question about working remotely in the hybrid work model. The study adapts the research procedures, including correlation, chi-square, and percentage analysis. Accepting the hybrid work style is crucial if you want to put the employees' long-term well-being first. The future workforce does appear to follow the mixed employment paradigm.

Read More...

This research presents the findings from an undergraduate research project concerning the environment friendly, manufacturing of plastic-carbon tile. This research focus on highlighting new and innovative methods that the quality of physical environment improves through the use of building techniques that enhance planning for environmental protection and advancement. It will provide a focus to improve sustainability in a global context. Industrialization is important for the development of country, but rapidly increase in the industrialization is giving rise to air pollution which is injurious to human health and atmosphere. Dumping the industrial residue is also not the solution to avoid pollution, as it leads to land pollution. To tackle this design and technology plays important role to give scalable solution. As tile is important construction material manufactured with the help of ceramic, clay, glass, cement. These are generally used to cover roofs, walls, floors. Because of the variation in design, color it is also used for decorative purpose the rapidly growing construction industry and world trade making the high tile production Replacement of raw material used in the ceramic tile with the industrial residue can be better solution to the society, crafting such tiles with the traditional method saves the five times energy as compare to ceramic tile. Manufacturing of such tile also gives the employment to those local communities who are unskilled to improve their standard of living.

Read More...

With varying plane ticket costs, domestic air travel is becoming increasingly popular in India. As more Internet booking channels emerge, passengers attempt to figure out how these airlines make decisions about ticket prices over time. Knowing the best travel time and the best spot to stay is also important. A sufficient amount is required. Unfortunately, dynamic pricing is typically implemented programmatically and is depending on specific hidden criteria (e.g., number of days till aircraft departure or number of tickets remaining). The research focuses on mining historical airfare data and using data modeling techniques to forecast price variations over time so that customers can benefit. This paper document study conducted to understand the traveling costs and will be helpful for the users to manage their entire traveling cost.

Read More...

Agriculture plays a major role in increasing the economic development of our nation. Crop production has greatly affected because of changes in weather pattern. Rising technologies is used to improve productivity of the crops by changing traditional farming to exactness farming. The key issue however to be resolved is cultivating precise crop at precise time. This could be through with the help machine learning algorithms that is found to be an efficient methodology for predicting the appropriate crop. The soil parameters like soil moisture and pH. Soil is that the base of agriculture. Soil provides nutrients that increase the expansion of a crop. Some chemical and physical properties of soil, like its moisture, pH, heavily have an effect on the yield of a crop. A soil watching and recommendation system is projected during which farmer are ready to monitor soil moisture, soil pH. The farmer will get the recommendations of crop on the idea of pH of the soil. The projected system is valid with t-test having no significance distinction between calibrated values and laboratory-recorded values. Victimization datasets from multiple sources, massive non-linear issues may well be simply solved by machine learning techniques. ML allows better decision making with tokenise human intervention in real-world eventualities. It provides a strong framework for historical data-driven higher cognitive process. For this answer we've used the Support Vector Machine (SVM) ml algorithm, it's extremely most well-liked by several because it produces vital accuracy with less computation power. It is used for each regression and classification tasks. Here classification of crop kind and crop weed is achieved by victimization SVM. ML techniques, like Convolution Neural Network (CNN) is used for extracting the relevant features in information.

Read More...

An adding number of people on twitter but hide their identity for nasty purpose. It's dangerous for other druggies hence the necessity for relating the twitter bots. therefore there's a developing need for distinguishing which regard contains bots or not. The characteristics of twitter accounts are employed as Features in machine literacy algorithms to marker druggies as genuine or fake. In this paper, we used three machine literacy algorithms to descry the account is fake or real, which are Decision Tree, Random Forest, and Multinomial Naive Bayes The delicacy given by the Decision tree algorithm is 93, the Random Forest algorithm is 90 and the Multinomial Naive Bayes is 89. numerous incidents have lately passed worldwide due to online importunity, similar as participating private exchanges, rumours, and sexual reflections. thus, the identification of bullying textbook or communication on social media has gained a growing quantum of attention among experimenters. The purpose of this exploration is to design and develop an effective fashion to descry online vituperative and bullying dispatches by incorporating natural language processing and machine literacy.

Read More...

Solution to above problem is to design and develop a continuous floating oil skimmer machine to reduce the idle time to a minimal value. The objective is to make a fully automatic machine which will solve above problem, this project also consist of renewable energy source i.e. solar panel to charge battery and also no maintenance required to run this machine.

Read More...

Turmeric is one of the important spice crops, which earns sizable foreign exchange for our country through export of its and products. By reducing the cost of production per hectare will result in increasing the benefit. The digging of turmeric crop at the proper maturity stage is an essential and important farm operation, but it is tedious, time consuming, labour intensive and costly. Also due to non – availability of skilled labour and the more wages demanded by them to digout the crop the higher field losses damage to the crop by manual digging, necessitate the need to develop a suitable mechanical tuber crop harvester for turmeric is developed based on need for the mechanization of the digging operation for turmeric crop. The tuber crop harvester consist of main frame, soil cutting blade, webs/windrowing unit and three point linkage.

Read More...

At present, vehicular collisions constitute the primary contributor to loss of life. The rise in vehicular fatalities has been observed to correspond with the growth in automobile manufacturing. Metropolitan areas also exhibit a heightened mortality rate due to a growing trend of negligence among individuals, resulting in severe consequences. The wide variety of transportation options available in contemporary times is believed to contribute significantly to the increased incidence of automobile accidents. The observed trend indicates a rise in both vehicular and passenger traffic with the growing number of automobiles utilizing the road networks. They present a potential hazard to both physiological and psychological systems. Thus, there exists a need for a dependable and feasible approach to automatic accident detection that leverages methodologies from the domain of image processing. In order to achieve this objective, the employed methodology involves the utilization of image normalization techniques, Convolutional Neural Networks (CNNs), and a Decision Tree algorithm for the purpose of detecting instances of cars accidents.

Read More...

The process of locating and notifying suspected malicious or anomalous behaviors within a specific system or environment is known as suspicious activity detection. This work is essential in a number of industries, including social media, finance, healthcare, and security. The examination of multiple data sources, including user behavior logs, network traffic, and sensor readings, using machine learning and data analytics techniques is the foundation for the detection of suspicious activities. The ultimate objectives are identifying and reducing security threats, stopping fraud, and enhancing system performance. An overview of the area of suspicious activity detection, its difficulties, and its applicability in numerous fields is given in this abstract. It emphasizes the significance of creating precise and effective algorithms to deal with the difficulties of spotting suspicious actions.

Read More...

In proposed work, we successfully implemented a news text summarization system using Natural Language Processing (NLP) techniques and the Latent Semantic Analysis (LSA) algorithm. The purpose of our project was to extract important information from a large volume of news articles and present it in a concise and easily understandable manner. To achieve this, we utilized the LSA algorithm, which is known for its ability to capture the underlying semantic structure of text. LSA employs a mathematical model to analyse relationships between words in a document, creating a semantic representation where words with similar contexts are grouped together in a vector space. The LSA-based summarization process involved several steps. First, we pre-processed the news articles by removing stop words, punctuation, and other non-relevant elements. Then, we constructed a term-document matrix, where rows represented words and columns represented documents, with matrix values representing word frequencies. Next, we applied Singular Value Decomposition (SVD) to the term-document matrix. SVD helped reduce the matrix's dimensionality by identifying the most important latent semantic concepts. This resulted in a lower-dimensional representation that captured the essential information. Finally, we identified the most important sentences in the news articles by measuring the cosine similarity between each sentence and the summary. Sentences with the highest cosine similarity scores were selected as summary sentences. The proposed system demonstrated the effectiveness of the LSA algorithm for news text summarization. By capturing the semantic structure of the text, it generated summaries that allowed users to understand the key points of a news article quickly and easily. Our implementation had practical applications for content recommendation systems, news aggregation platforms, and personalized news feeds. However, it is important to acknowledge the limitations of the LSA algorithm. It may struggle with handling idiomatic expressions and can be sensitive to the quality of the input data. These considerations highlight the need for ongoing research and development to enhance the performance and robustness of news text summarization systems.

Read More...

Compared to traditional methods, the Internet infrastructure has undergone enormous advancements. The internet is a strategy for building a world in which all objects, people, and services are linked to one another and capable of interacting and working together to aid in the gathering, storing, exchanging, and monitoring of data. Therefore, extra care and protection are needed for extremely confidential patient health information. The availability and affordability of the Internet have created the rise of a healthcare trend known as e-healthcare. The steganographic algorithm LSB is used to encrypt patient health information/prescription which is embedded in a digital host before begin sent to the network, thus their existence is uncertain in nature. In addition to adding an extra layer of security, the cryptographic algorithm MD5 Hash function enables the validation process from the stego image to decrypt the patient's health information/prescription and MRI images. In the case of text data, the base 64 encoding algorithm will be used to encode and store text data in the database. Two things will be checked, the image will be decrypted, if there is an MRI in the database and else the data will be unlocked if not. After verification, the health information and prescription for the patient will be recovered. Future research will expand this to include a variety of applications, including one-time password security, mobile apps, cloud implementation, multiple access, and online appointment integrations.

Read More...