Exam Paper Generator provides a solution to choose challenging, well framed questions and make it easy for the instructor to generate it within a short period of time. This can be done in a few taps of the hand as it is an Android application, therefore accessible at any time and place. It contains various modules which enables the system to deal with all questions easily. The modules like admin module, user module, and question entry and question management makes it an effortless task. From the entered input the paper is generated and saved as a .pdf file which can be kept for own or distributed as per the user or admin requirements. Android projects app ideas for students Android base order recommender system This system stores data via MySQL database, develops server-end background management system used by merchants via Eclipse, and utilizes Tomcat to establish the server to realize functions such as merchant login and registration, dish addition, dish modification and deletion, order management and deletion, and merchant information alteration. At the client end, Android Studio is used to plan UI elaborately, and realize functions such as user login and registration, restaurant browsing, dish browsing, shopping cart, user information change, and online ordering. Finally, Android-based order recommender system with the favorable interactive interface is realized, and able to work in good conditions. eBus – Geo Location Tracking System for BusAdvanced traveler information systems are one component of intelligent transportation systems, and a major component is travel time information. Prediction Model have been adopted by many transit agencies for tracking their vehicles and predicting travel time in real time. It is a very important subject to improve the precision and reliability of the prediction model which can attract additional ridership, reduce passengers’ anxieties and waiting times at bus stop, and increase their satisfaction. Furthermore, it can promote the development of city public transportation. This paper presents an improved approach to predict the public bus arrival time based on location. After analyzing the components of bus arrival time systematically, the bus arrival time and dwell time at previous stops are chosen as the main input variables of the prediction model. At first, the algorithm of data interpolation and processing is designed to get the real-time of bus arrival as the input variables of the prediction models. Secondly, the statistical model is obtained based on the filtering the location, bus route and date of each bus respectively. Thirdly, a hybrid prediction model is proposed to predict the bus arrival time. The results show that the improved model out performs the historical data based model in terms of prediction accuracy. Health Diet Online Search And Proposal SystemMedical study has revealed that people set a bigger possibility of countering free radicals and warding off illness by consumption of healthy foods and by increasing their resistant system. Due to the poor eating habits people suffer from many diseases. In the current scenario fast food become important food in daily routine because it is effortlessly available but taking fast food in routine may cause for disease like heart attack, diabetics etc. Healthier diets help us to maintain our health and keep us away from many diseases. For better recovery from diseases or surgery etc individual have special needs according to their medical profile, cultural backgrounds and nutrient requirements. Design and implementation of healthy diet recommendation system is based on web data mining which is the application of data mining technique help us to determine pattern from web.Adversarial Learning In Credit Card Fraud DetectionCredit card fraud is an expensive problem for many financial institutions, costing billions of dollars to companies annually. Many adversaries still evade fraud detection systems because these systems often do not include information about the adversary’s knowledge of the fraud detection mechanism. This project aims to include information about the “fraudster’s” motivations and knowledge base into an adaptive fraud detection system. In this project, we use a game theoretical adversarial learning approach in order to model the fraudster’s best strategy and pre-emptively adapt the fraud detection system to better classify these future fraudulent transactions. Using a logistic regression classifier as the fraud detection mechanism, we initially identify the best strategy for the adversary based on the number of fraudulent transactions that go undetected, and assume that the adversary uses this strategy for future transactions in order to improve our classifier. Prior research has used game theoretic models for adversarial learning in the domains of credit card fraud and email spam, but this project adds to the literature by extending these frameworks to a practical, real-world data set. Test results show that our adversarial framework produces an increasing AUC score on validation sets over several iterations in comparison to the static model usually employed by credit card companies. EGG Production Management SystemPoultry Farm Management System has been developed for giving various information of the poultry farm. This application is mainly for the maintenance and management of the poultry farm. It maintains the record systematically and enables us to give information in time. A Food Wastage Reduction Mobile ApplicationAbstract— Wasting food is a common problem in our society. Food waste management is crucial since it can improve our environmental and economic sustainability. We have identified the use of mobile technology to reduce food waste management and built an android mobile application that allows restaurants to donate and share their foods and leftovers with people in need. This app will enable users to register, login, view items, add items, add items to cart, remove an item from the cart, and log out. This app is using the firebase storage and real-time database. Any user in need can see all the food images donated by different users and add it to his or her cart. https://twitter.com/codeshoppy https://facebook.com/codeshoppy
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