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Articles 1 - 30 of 60
Full-Text Articles in Physical Sciences and Mathematics
Protecting And Maintaining Silicon Valley’S Liquid Gold, Paul Mark Fulcher
Protecting And Maintaining Silicon Valley’S Liquid Gold, Paul Mark Fulcher
Master's Projects
Public sector leaders and decision makers in the California water industry have learned from previous severe drought conditions that to sustain water supplies during extremely dry seasons, there is a substantial need for behavioral changes associated with water conservation efforts among the businesses and residents of the community to maintain an adequate water supply. The intent of this study is to compare four California water agencies that have been designated as sustainable groundwater agencies (GSA), and determine what current programs and/or practices those agencies are using to meet the mandated requirements of the Sustainable Groundwater Management Act of 2014 (Act …
Detecting Encrypted Malware Using Hidden Markov Models, Dhiviya Dhanasekar
Detecting Encrypted Malware Using Hidden Markov Models, Dhiviya Dhanasekar
Master's Projects
Encrypted code is often present in some types of advanced malware, while such code virtually never appears in legitimate applications. Hence, the presence of encrypted code within an executable file could serve as a strong heuristic for detecting malware. In this research, we consider the feasibility of detecting encrypted code using hidden Markov models.
Multi Language Browser Support, Swapnil Mohan Patil
Multi Language Browser Support, Swapnil Mohan Patil
Master's Projects
Web browsers have become an increasingly appealing platform for application developers. Browsers make it relatively easy to deliver cross-platform applications. Web browsers have become a de facto universal operating system, and JavaScript its instruction set. Unfortunately, executing any other language than JavaScript in web browser is not usually possible. Previous approaches are either non-portable or demand extensive modifications for programs to work in the browser. Translation to JavaScript (JS) is one option but that can be challenging if the language is sufficiently different from JS. Also, debugging translated applications can be difficult. This paper presents how languages like Scheme and …
“Bluff” With Ai, Tina Philip
“Bluff” With Ai, Tina Philip
Master's Projects
The goal of this project is to build multiple agents for the game Bluff and to conduct experiments as to which performs better. Bluff is a multi-player, non-deterministic card game where players try to get rid of all the cards in their hand. The process of bluffing involves making a move such that it misleads the opponent and thus prove to be of advantage to the player. The strategic complexity in the game arises due to the imperfect or hidden information which means that certain relevant details about the game are unknown to the players. Multiple agents followed different strategies …
Cache Management And Load Balancing For 5g Cloud Radio Access Networks, Chin Tsai
Cache Management And Load Balancing For 5g Cloud Radio Access Networks, Chin Tsai
Master's Projects
Cloud radio access network (CRAN) has been proposed for 5G mobile networks. The benefit of a CRAN includes better scalability, flexibility, and performance. The paper introduces a cache management algorithm for a baseband unit of CRAN and load balancing algorithms for virtual machines load within the CRAN. The proposed scheme, exponential decay (EXD) with analytical hierarchy process (AHP), increases hit rate and reduces network traffic. The scheme also provides preferential services for users with a higher service level agreement (SLA). Finally, the experiment shows the proposed load balancing algorithm can reduce the virtual machines’ (VM) queue size and wait time.
Implementation Of Faceted Values In Node.Js., Andrew Kalenda
Implementation Of Faceted Values In Node.Js., Andrew Kalenda
Master's Projects
Information flow analysis is the study of mechanisms by which developers may protect sensitive data within an ecosystem containing untrusted third-party code. Secure multi-execution is one such mechanism that reliably prevents undesirable information flows, but a programmer’s use of secure multi-execution is itself challenging and prone to error. Faceted values have been shown to provide an alternative to secure multi-execution which is, in theory, functionally equivalent. The purpose of this work is to show that the theory holds in practice by implementing usable faceted values in JavaScript via source code transformation. The primary contribution of this project is to provide …
A Scrabble Artificial Intelligence Game, Priyatha Joji Abraham
A Scrabble Artificial Intelligence Game, Priyatha Joji Abraham
Master's Projects
Computer AI players have already surpassed human opponents in competitive Scrabble, however, defeating a Computer AI opponent is complex and demands efficient heuristics. The primary objective of this project is to build two intelligent AI players from scr atch for the Scrabble cross - board puzzle game having different move generation heuristics and endgame strategies to evaluate their performance based on various benchmarks like winning criteria, quality of moves, and time consumption. The first AI selected is the most popular Scrabble AI, Maven. It generates a three - ply look - ahead simulation to evaluate the most promising candidate move …
Measuring The Effectiveness Of Generic Malware Models, Naman Bagga
Measuring The Effectiveness Of Generic Malware Models, Naman Bagga
Master's Projects
Malware detection based on machine learning techniques is often treated as a problem specific to a particular malware family. In such cases, detection involves training and testing models for each malware family. This approach can generally achieve high accuracy, but it requires many classification steps, resulting in a slow, inefficient, and impractical process. In contrast, classifying samples as malware or be- nign based on a single model would be far more efficient. However, such an approach is extremely challenging—extracting common features from a variety of malware fam- ilies might result in a model that is too generic to be useful. …
Bootbandit: A Macos Bootloader Attack, Armen Boursalian
Bootbandit: A Macos Bootloader Attack, Armen Boursalian
Master's Projects
Full disk encryption (FDE) is used to protect a computer system against data theft by physical access. If a laptop or hard disk drive protected with FDE is stolen or lost, the data remains unreadable without the encryption key. To foil this defense, an intruder can gain physical access to a computer system in a so-called “evil maid” attack, install malware in the boot (pre-operating system) environment, and use the malware to intercept the victim’s password. Such an attack relies on the fact that the system is in a vulnerable state before booting into the operating system. In this paper, …
Cache Management Schemes For User Equipment Contexts In 5th Generation Cloud Radio Access Networks, Gurpreet Kaur
Cache Management Schemes For User Equipment Contexts In 5th Generation Cloud Radio Access Networks, Gurpreet Kaur
Master's Projects
Advances in cellular network technology continue to develop to address increasing demands from the growing number of devices resulting from the Internet of Things, or IoT. IoT has brought forth countless new equipment competing for service on cellular networks. The latest in cellular technology is 5th Generation Cloud Radio Access Networks, or 5G C-RAN, which consists of an architectural design created specifically to meet novel and necessary requirements for better performance, reduced latency of service, and scalability. As part of this design is the inclusion of a virtual cache, there is a necessity for useful cache management schemes and protocols, …
Time-Efficient Hybrid Approach For Facial Expression Recognition, Roshni Velluva Puthanidam
Time-Efficient Hybrid Approach For Facial Expression Recognition, Roshni Velluva Puthanidam
Master's Projects
Facial expression recognition is an emerging research area for improving human and computer interaction. This research plays a significant role in the field of social communication, commercial enterprise, law enforcement, and other computer interactions. In this paper, we propose a time-efficient hybrid design for facial expression recognition, combining image pre-processing steps and different Convolutional Neural Network (CNN) structures providing better accuracy and greatly improved training time. We are predicting seven basic emotions of human faces: sadness, happiness, disgust, anger, fear, surprise and neutral. The model performs well regarding challenging facial expression recognition where the emotion expressed could be one of …
Word Sense Determination From Wikipedia Data Using Neural Networks, Qiao Liu
Word Sense Determination From Wikipedia Data Using Neural Networks, Qiao Liu
Master's Projects
Many words have multiple meanings. For example, “plant” can mean a type of living organism or a factory. Being able to determine the sense of such words is very useful in natural language processing tasks, such as speech synthesis, question answering, and machine translation. For the project described in this report, we used a modular model to classify the sense of words to be disambiguated. This model consisted of two parts: The first part was a neural-network-based language model to compute continuous vector representations of words from data sets created from Wikipedia pages. The second part classified the meaning of …
Virtualized Baseband Units Consolidation In Advanced Lte Networks Using Mobility- And Power-Aware Algorithms, Uladzimir Karneyenka
Virtualized Baseband Units Consolidation In Advanced Lte Networks Using Mobility- And Power-Aware Algorithms, Uladzimir Karneyenka
Master's Projects
Virtualization of baseband units in Advanced Long-Term Evolution networks and a rapid performance growth of general purpose processors naturally raise the interest in resource multiplexing. The concept of resource sharing and management between virtualized instances is not new and extensively used in data centers. We adopt some of the resource management techniques to organize virtualized baseband units on a pool of hosts and investigate the behavior of the system in order to identify features which are particularly relevant to mobile environment. Subsequently, we introduce our own resource management algorithm specifically targeted to address some of the peculiarities identified by experimental …
Improve And Implement An Open Source Question Answering System, Salil Shenoy
Improve And Implement An Open Source Question Answering System, Salil Shenoy
Master's Projects
A question answer system takes queries from the user in natural language and returns a short concise answer which best fits the response to the question. This report discusses the integration and implementation of question answer systems for English and Hindi as part of the open source search engine Yioop. We have implemented a question answer system for English and Hindi, keeping in mind users who use these languages as their primary language. The user should be able to query a set of documents and should get the answers in the same language. English and Hindi are very different when …
Aria A11y Analyzer: Helping Integrate Accessibility Into Websites, Jayashree Prabunathan
Aria A11y Analyzer: Helping Integrate Accessibility Into Websites, Jayashree Prabunathan
Master's Projects
Today, nearly 1 in 5 people have a disability that affects their daily life. These varied disabilities can include blindness, low vision or mobility impairments. When interacting with web content, users with such disabilities rely heavily on various assistive technologies, such as screen readers, keyboard, voice recognition software, etc. Here, assistive technologies are software applications or hardware devices that allows users with disabilities to interact with web and software applications. For instance, a screen reader is a software application that navigates through the page and speaks the content to users. Web accessibility is defined as the ability for assistive technology …
Metamorphic Code Generation Using Llvm, Michael Crawford
Metamorphic Code Generation Using Llvm, Michael Crawford
Master's Projects
Each instance of metamorphic software changes its internal structure, but the function remains essentially the same. Such metamorphism has been used primarily by malware writers as a means of evading signature-based detection. However, metamorphism also has potential beneficial uses in fields related to software protection. In this research, we develop a practical framework within the LLVM compiler that automatically generates metamorphic code, where the user has well-defined control over the degree of morphing applied to the code. We analyze the effectiveness of this metamorphic generator based on Hidden Markov Model (HMM) analysis, and discover that HMMs are effective at detection …
Question Type Recognition Using Natural Language Input, Aishwarya Soni
Question Type Recognition Using Natural Language Input, Aishwarya Soni
Master's Projects
Recently, numerous specialists are concentrating on the utilization of Natural Language Processing (NLP) systems in various domains, for example, data extraction and content mining. One of the difficulties with these innovations is building up a precise Question and Answering (QA) System. Question type recognition is the most significant task in a QA system, for example, chat bots. Organization such as National Institute of Standards (NIST) hosts a conference series called as Text REtrieval Conference (TREC) series which keeps a competition every year to encourage and improve the technique of information retrieval from a large corpus of text. When a user …
Improving Text Classification With Word Embedding, Lihao Ge
Improving Text Classification With Word Embedding, Lihao Ge
Master's Projects
One challenge in text classification is that it is hard to make feature reduction basing upon the meaning of the features. An improper feature reduction may even worsen the classification accuracy. Word2Vec, a word embedding method, has recently been gaining popularity due to its high precision rate of analyzing the semantic similarity between words at relatively low computational cost. However, there are only a limited number of researchers focusing on feature reduction using Word2Vec. In this project, we developed a Word2Vec based method to reduce the feature size while increasing the classification accuracy. The feature reduction is achieved by loosely …
Housing Price Prediction Using Support Vector Regression, Jiao Yang Wu
Housing Price Prediction Using Support Vector Regression, Jiao Yang Wu
Master's Projects
The relationship between house prices and the economy is an important motivating factor for predicting house prices. Housing price trends are not only the concern of buyers and sellers, but it also indicates the current economic situation. Therefore, it is important to predict housing prices without bias to help both the buyers and sellers make their decisions. This project uses an open source dataset, which include 20 explanatory features and 21,613 entries of housing sales in King County, USA. We compare different feature selection methods and feature extraction algorithm with Support Vector Regression (SVR) to predict the house prices in …
Path-Finding Methodology For Visually-Impaired Patients Based On Image-Processing, Abhilash Goyal
Path-Finding Methodology For Visually-Impaired Patients Based On Image-Processing, Abhilash Goyal
Master's Projects
The objective of this project is to propose and develop the path-finding methodology for the visually impaired patients. The proposed novel methodology is based on image-processing and it is targeted for the patients who are not completely blind. The major problem faced by visually impaired patients is to walk independently. It is mainly because these patients can not see obstacles in front of them due to the degradation in their eye sight. Degradation in the eye-sight is mainly because either the light doesn't focus on the retina properly or due to the malfunction of the photoreceptor cells on the retina, …
Adding Differential Privacy In An Open Board Discussion Board System, Pragya Rana
Adding Differential Privacy In An Open Board Discussion Board System, Pragya Rana
Master's Projects
This project implements a privacy system for statistics generated by the Yioop search and discussion board system. Statistical data for such a system consists of various counts, sums, and averages that might be displayed for groups, threads, etc. When statistical data is made publicly available, there is no guarantee of preserving the privacy of an individual. Ideally, any data extracted should not reveal any sensitive information about an individual. In order to help achieve this, we implemented a Differential Privacy mechanism for Yioop. Differential privacy preserves privacy up to some controllable parameters of the number of items or individuals being …
Predicting Pancreatic Cancer Using Support Vector Machine, Akshay Bodkhe
Predicting Pancreatic Cancer Using Support Vector Machine, Akshay Bodkhe
Master's Projects
This report presents an approach to predict pancreatic cancer using Support Vector Machine Classification algorithm. The research objective of this project it to predict pancreatic cancer on just genomic, just clinical and combination of genomic and clinical data. We have used real genomic data having 22,763 samples and 154 features per sample. We have also created Synthetic Clinical data having 400 samples and 7 features per sample in order to predict accuracy of just clinical data. To validate the hypothesis, we have combined synthetic clinical data with subset of features from real genomic data. In our results, we observed that …
An Open Source Discussion Group Recommendation System, Sarika Padmashali
An Open Source Discussion Group Recommendation System, Sarika Padmashali
Master's Projects
A recommendation system analyzes user behavior on a website to make suggestions about what a user should do in the future on the website. It basically tries to predict the “rating” or “preference” a user would have for an action. Yioop is an open source search engine, wiki system, and user discussion group system managed by Dr. Christopher Pollett at SJSU. In this project, we have developed a recommendation system for Yioop where users are given suggestions about the threads and groups they could join based on their user history. We have used collaborative filtering techniques to make recommendations and …
Neural Net Stock Trend Predictor, Sonal Kabra
Neural Net Stock Trend Predictor, Sonal Kabra
Master's Projects
This report analyzes new and existing stock market prediction techniques. Traditional technical analysis was combined with various machine-learning approaches such as artificial neural networks, k-nearest neighbors, and decision trees. Experiments we conducted show that technical analysis together with machine learning can be used to profitably direct an investor’s trading decisions. We are measuring the profitability of experiments by calculating the percentage weekly return for each stock entity under study. Our algorithms and simulations are developed using Python. The technical analysis methodology combined with machine learning algorithms show promising results which we discuss in this report.
Web - Based Office Market, Manodivya Kathiravan
Web - Based Office Market, Manodivya Kathiravan
Master's Projects
People who work in an office often have different pools of resources that they want to exchange. They want to trade their resources/work(seller) with a person who wants that particular resource(buyer) and in return get another resource the buyer offers. These kind of exchanges are often called Barter-exchanges where an item is traded for another item without the involvement of actual money. An exchange is set to be complete when there is a match between an available item and a desired item. This exchange is called direct exchange. When an item desired by one user is made available through a …
Ai For Classic Video Games Using Reinforcement Learning, Shivika Sodhi
Ai For Classic Video Games Using Reinforcement Learning, Shivika Sodhi
Master's Projects
Deep reinforcement learning is a technique to teach machines tasks based on trial and error experiences in the way humans learn. In this paper, some preliminary research is done to understand how reinforcement learning and deep learning techniques can be combined to train an agent to play Archon, a classic video game. We compare two methods to estimate a Q function, the function used to compute the best action to take at each point in the game. In the first approach, we used a Q table to store the states and weights of the corresponding actions. In our experiments, this …
Document Classification Using Machine Learning, Ankit Basarkar
Document Classification Using Machine Learning, Ankit Basarkar
Master's Projects
To perform document classification algorithmically, documents need to be represented such that it is understandable to the machine learning classifier. The report discusses the different types of feature vectors through which document can be represented and later classified. The project aims at comparing the Binary, Count and TfIdf feature vectors and their impact on document classification. To test how well each of the three mentioned feature vectors perform, we used the 20-newsgroup dataset and converted the documents to all the three feature vectors. For each feature vector representation, we trained the Naïve Bayes classifier and then tested the generated classifier …
Credit Scoring Using Logistic Regression, Ansen Mathew
Credit Scoring Using Logistic Regression, Ansen Mathew
Master's Projects
This report presents an approach to predict the credit scores of customers using the Logistic Regression machine learning algorithm. The research objective of this project is to perform a comparative study between feature selection and feature extraction, against the same dataset using the Logistic Regression machine learning algorithm. For feature selection, we have used Stepwise Logistic Regression. For feature extraction, we have used Singular Value Decomposition (SVD) and Weighted Singular Value Decomposition (SVD). In order to test the accuracy obtained using feature selection and feature extraction, we used a public credit dataset having 11 features and 150,000 records. After performing …
Community Detection In Social Networks, Ketki Kulkarni
Community Detection In Social Networks, Ketki Kulkarni
Master's Projects
The rise of the Internet has brought people closer. The number of interactions between people across the globe has gone substantially up due to social awareness, the advancements of the technology, and digital interaction. Social networking sites have built societies, communities virtually. Often these societies are displayed as a network of nodes depicting people and edges depicting relationships, links. This is a good and e cient way to store, model and represent systems which have a complex and rich information. Towards that goal we need to nd e ective, quick methods to analyze social networks. One of the possible solution …
Switching Between Page Replacement Algorithms Based On Work Load During Runtime In Linux Kernel, Praveen Subramaniyam
Switching Between Page Replacement Algorithms Based On Work Load During Runtime In Linux Kernel, Praveen Subramaniyam
Master's Projects
Today’s computers are equipped with multiple processor cores to execute multiple programs effectively at a single point of time. This increase in the number of cores needs to be equipped with a huge amount of physical memory to keep multiple applications in memory at a time and to effectively switch between them, without getting affected by the low speed disk memory. The physical memory of today’s world has become so cheap such that all the computer systems are always equipped with sufficient amount of physical memory required effectively to run most of the applications. Along with the memory, the sizes …