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- Creator:
- Mehta, Ratna
- Description:
- This application helps to take attendance for every course which will help to reduce the manual procedure of taking the attendance.
- Resource Type:
- Project
- Campus Tesim:
- Sacramento
- Department:
- Computer Science
- Creator:
- Ponugoti, Suraj
- Description:
- This project is about exporting physical SCSI devices on server side to initiator side over iSCSI through CAM Target Layer as an actual SCSI Target
- Resource Type:
- Project
- Campus Tesim:
- Sacramento
- Department:
- Computer Science
3. Plug-in for singleton service in clustered environment and improving failure detection methodology
- Creator:
- Kodali, Srinivasa Chakravarthy
- Description:
- As all web applications these days are mostly clustered, thus singleton service is very much needed. In clustered environment we loose the ability of singleton objects. so singleton service can be used to makes sure that singleton objects are available to each node in cluster. Plug-in helps to create a singleton service in any clustered application.
- Resource Type:
- Project
- Campus Tesim:
- Sacramento
- Department:
- Computer Science
- Creator:
- Karnik, Shweta
- Description:
- Requirements Analysis is a critical task in the software development lifecycle. System requirements must be accurately interpreted, captured and documented to ensure successful software product development and delivery. The aim of this project is to design a web-based tool to capture, document, track and analyze requirements using UML Use Case models. This system is designed to be intuitive, robust and is implemented in Ruby on Rails and MySQL database.
- Resource Type:
- Project
- Campus Tesim:
- Sacramento
- Department:
- Computer Science
5. Cloud Drop
- Creator:
- Dhondaley, Preetham V.
- Description:
- CloudDrop proposes to provide a quality system to support cross-platform file transfer mechanism between Android and IOS devices with cloud storage. The devices include iPhones, iPads, Android phones, and Android tablets. The current status of this application and the approaches used to solve some of the critical problems and features are presented in this report.
- Resource Type:
- Project
- Campus Tesim:
- Sacramento
- Department:
- Computer Science
- Creator:
- Rond, Thomas Richard
- Description:
- Today's popular asymmetric cryptosystems are vulnerable to quantum attacks. I read multiple GGH research papers. I implemented four GGH-based cryptosystems. Lattice problems are promising quantum-resistant cryptographic primitives, but further developments are required before they can be considered secure and practical.
- Resource Type:
- Project
- Campus Tesim:
- Sacramento
- Department:
- Computer Science
- Creator:
- Rajguru, Aniruddha Shekhar
- Description:
- Over the years, data privacy has been a major concern amongst consumers. Applications such as Facebook, Uber, and Instagram collect a huge amount of data from users in return for the free service. Some of this data collection is necessary for the service to work. However, the data being collected is often not essential for the functionality but is rather used for targeted advertising or user analytics. As the data collection takes place in the background, most consumers are left clueless. Consumers also lack the technical expertise to identify such data collection. Not just third-party applications, but even the Android operating system itself sometimes violates users’ privacy heavily. There are various ways of collecting user data, one of which is using device sensors, such as microphones, cameras, GPS, Wi-Fi and accelerometer, to precisely monitor the users’ activity. The goal of this project is to create a sensor monitor that allows users to view and capture accurately what happens to their data on a day-to-day basis. The sensor monitor also informs users to view which applications are accessing which sensors and at what time. To achieve this functionality, the sensor monitor targets three parts of the Android stack: the Linux kernel’s PROC file system, Android’s SensorManager utility, and sensor.h header file. Combining these metrics along with a flag status allows the sensor monitor to form historical insights and send real-time alerts. The sensor monitor is designed to be modular for better maintainability and extensibility. All sensor monitor insights are stored in JSON and can be easily exported for further analysis. Thus, the sensor monitor will benefit a regular smartphone user as well as form a base for future projects in the Android domain.
- Resource Type:
- Project
- Campus Tesim:
- Sacramento
- Department:
- Computer Science
- Creator:
- Luman, Rijul
- Description:
- Since the rise of internet and e-commerce, buying and selling goods over the internet has relied heavily on financial institutions acting as 3rd parties to process financial transactions. These 3rd parties often charge a good percentage of the payment as transaction fees and often take days to complete. These processes are therefore based upon the 2 parties trusting a 3rd party to process their transaction, and as a 3rd party must be “trusted” there is always room for a transaction to be reversed. Before Bitcoin, there was no way to make a non-reversible payment online for a non-reversible service as there is with cash in the physical world. With the recent price rise of Bitcoin, we have witnessed the impact a decentralized digital currency can have on the world. Mining Bitcoins require special hardware; thus, I have developed a coin using JavaScript, which can be mined on any device with minimal overhead. All services are accessible via REST APIs to the Full Node. This project contains the following features: 1. Ability to create a new Public/Private Key pairs (Wallet address). 2. A blockchain which maintains all the transactions and acts as a Ledger. 3. Ability to update the blockchain and manage forks in the blockchain. 4. Send and receive coins. Each coin can be split up to 6 decimal places. 5. Ability to check any wallet’s balance, using its public key. 6. Ability to connect to other full nodes via the internet. 7. Miner Software, which will process all the unconfirmed transactions.
- Resource Type:
- Project
- Campus Tesim:
- Sacramento
- Department:
- Computer Science
- Creator:
- Kollu, Sindhu
- Description:
- In modern economic times, everyone wants to save their money and keep expenses with in their budget limit. But, due to our busy schedules in our day to day life, we may lose track of our expenses and end up overspending which leads to debts. In this project, the aim is to develop a mobile application which helps user to keep track of all the expenses and to simplify the tracking process. The proposed system will also generate detailed information on which category of shopping we are exceeding our budgets so that the user can monitor and keep his expenses with in his budget limit. The rapid growth in technology has led to smart mobile applications development. The proposed application utilizes Optical Character Recognition(OCR) engine to scan the shopping receipts and extract the data such as merchant name, merchant type, date of purchase and the amount spent on each shopping item on any specific day. Optical character recognition is a technique to convert any printed text or document into digital text. The data extracted after performing OCR is then visualized using various insightful charts and reports which will help the users to estimate and keep track of their expenses to be within the budget limit. Smart budget assistant is an Android mobile application which simplifies the process of entering expenses and tracking them to help users keep their expenses with in their budgets by informing about their limits and visualizing detailed reports for quick analysis to save time and money.
- Resource Type:
- Project
- Campus Tesim:
- Sacramento
- Department:
- Computer Science
- Creator:
- Jain, Anshul
- Description:
- Indoor localization has become one of the most talked about services in today’s technology. We have observed that there have been huge demand of Indoor Location services due to increase in smartphone market in last few years. GPS is widely used to find the real time location information of different mobile users mainly in outdoors. This is the main reason there is a large demand for real time location prediction of various mobile users. However, GPS is not effective in indoor buildings due to its weak signal strength and has been found in the research that GPS does not work properly in indoor environment. Wi-Fi access points are widely used in indoor localization techniques which are based on Wi-Fi fingerprint data. Many research papers have been proposed on Wi-Fi fingerprinting based methods using its signal strength generated from Wi-Fi access points. They have proposed that Wi-Fi fingerprinting can increase indoor localization accuracy using different methods like collected Wi-Fi signal strength in various locations. Indoor localization using machine learning techniques is still an open area in which so much research is still going on to find out the best indoor localization. Our goal in this project is to do the comparative analysis of indoor localization using the different machine learning models. We will collect Wi-Fi fingerprinting data which has different Wi-Fi signal strength, and access points on different locations using android application in an android smartphone Motorola G4. After then, we will implement and evaluate the indoor positioning accuracy, time complexity and test error on different machine learning/ neural network models. We will present the comparative analysis of best model out of them to use for indoor localization technique in various closed environment. This project will be implemented on the third floor of California state university- Sacramento, Department of computer science after collecting the Wi-Fi fingerprinting data and will perform different test results. We have also found there has not been much research and comparative analysis happened in indoor localization field using the different machine learning algorithms in different scenarios like time duration, accuracy, error and overall performance. Implementation will be done in both the environments CPU and GPU using python programming language and different related libraries.
- Resource Type:
- Project
- Campus Tesim:
- Sacramento
- Department:
- Computer Science