Computer Sciences Commons^™

Yioop Full Historical Indexing In Cache Navigation, Akshat Kukreti

Master's Projects

This project adds new cache-related features to Yioop, an Open Source, PHP-based search engine. Search engines often maintain caches of pages downloaded by their crawler. Commercial search engines like Google display a link to the cached version of a web page along with the search results for that particular web page. The first feature enables users to navigate through Yioop's entire cache. When a cached page is displayed along with its contents, links to cached pages saved in the past are also displayed. The feature also enables users to navigate cache history based on year and month. This feature is …

Modular Approach To Big Data Using Neural Networks, Animesh Dutta

Master's Projects

Machine learning can be used to recognize patterns, classify data into classes and make predictions. Neural Networks are one of the many machine learning tools that are capable of performing these tasks. The greatest challenges that we face while dealing with the IBM Watson dataset is the high amount of dimensionality, both in terms of the number of features the data has, as well the number of rows of data we are dealing with. The aim of the project is to identify a course of action that can be chosen when dealing with similar problems. The project aims at setting …

Analysis Of Parallel Montgomery Multiplication In Cuda, Yuheng Liu

Master's Projects

For a given level of security, elliptic curve cryptography (ECC) offers improved efficiency over classic public key implementations. Point multiplication is the most common operation in ECC and, consequently, any significant improvement in perfor- mance will likely require accelerating point multiplication. In ECC, the Montgomery algorithm is widely used for point multiplication. The primary purpose of this project is to implement and analyze a parallel implementation of the Montgomery algorithm as it is used in ECC. Specifically, the performance of CPU-based Montgomery multiplication and a GPU-based implementation in CUDA are compared.

Big Data Classification Using Decision Trees On The Cloud, Chinmay Bhawe

Master's Projects

This writing project addresses the topic of attempting to use machine learning on very large data sets on cloud servers. The project consists of two phases. The first being developing a machine learning system which will learn on the data provided by IBM for the “IBM Watson Great minds Challenge SJSU Pilot” competition and providing the best possible results on the evaluation data set, also provided by the IBM Watson team. This will serve as a basis for the second phase of the project, in which the objective is to move the machine learning system on to a cloud server, …

Mobile Presentation Of Unstructured Information, Shailesh Benake

Master's Projects

Since the advent of online education in 1994 by CALCampus , many improvements have been made for effectiveness of e-learning. Video/audio conferencing, synchronous education system and many such advances in multimedia communication have made this system more popular among the masses. However with many online education websites, competing to make the same course, it’s important for user to find course structure of his interest. What makes even more challenging for a learner is, to decide how good will be the learning from a course provided by a particular site. For example open online course sites like edx.org, canvas.net, coursera.org etc …

Big Data Analysis Using Amazon Web Services And Support Vector Machines, Dhruv Jalota

Master's Projects

This writing project aims to apply the supervised machine learning technique known as Support Vector Machines to a large labeled data set, to attempt to classify an unlabeled data set using the result of training on the labeled data set, and hence perform an analysis of the various results obtained using different Amazon Elastic Cloud Compute instances, sizes of input data set, and different parameters or kernels of the SVM tool. The given data set is relatively large for SVM and the tool being used, known as libsvm, having approximately 1.3 million training examples and 341 attributes with binary classification …

Vistruclizer: A Structural Visualizer For Multi-Dimensional Social Networks, Bingtian Dai, Agus Trisnajaya Kwee, Ee Peng Lim

Research Collection School Of Computing and Information Systems

With the popularity of Web 2.0 sites, social networks today increasingly involve different kinds of relationships among different types of users in a single network. Such social networks are said to be multi-dimensional. Analyzing multi-dimensional networks is a challenging research task that requires intelligent visualization techniques. In this paper, we therefore propose a visual analytics tool called ViStruclizer to analyze structures embedded in a multi-dimensional social network. ViStruclizer incorporates structure analyzers that summarize social networks into both node clusters each representing a set of users, and edge clusters representing relationships between users in the node clusters. ViStruclizer supports user interactions …

Cloud Storage Performance And Security Analysis With Hadoop And Gridftp, Wei-Li Liu

Master's Projects

Even though cloud server has been around for a few years, most of the web hosts today have not converted to cloud yet. If the purpose of the cloud server is distributing and storing files on the internet, FTP servers were much earlier than the cloud. FTP server is sufficient to distribute content on the internet. Therefore, is it worth to shift from FTP server to cloud server? The cloud storage provider declares high durability and availability for their users, and the ability to scale up for more storage space easily could save users tons of money. However, does it …

Recommendation System For News Reader, Shweta Athalye

Master's Projects

Recommendation Systems help users to find information and make decisions where they lack the required knowledge to judge a particular product. Also, the information dataset available can be huge and recommendation systems help in filtering this data according to users‟ needs. Recommendation systems can be used in various different ways to facilitate its users with effective information sorting. For a person who loves reading, this paper presents the research and implementation of a Recommendation System for a NewsReader Application using Android Platform. The NewsReader Application proactively recommends news articles as per the reading habits of the user, recorded over a …

Cloud Services For An Android Based Home Security System, Karthik Challa

Master's Projects

This report talks in detail about an android based application designed for a home security system. The home security system is a tablet device developed using the android framework. The home security system makes use of sensors and a central device to secure an area. Currently the devices are standalone and require the users to be physically present to operate the devices with no interaction possible between two different devices. The system is also limited by its computational resources and storage capacity. For this project, I have developed a cloud based client server architecture to address these limitations and also …

Http Attack Detection Using N-Gram Analysis, Adityaram Oza

Master's Projects

Previous research has shown that byte level analysis of HTTP traffic offers a practical solution to the problem of network intrusion detection and traffic analysis. Such an approach does not require any knowledge of applications running on web servers or any pre-processing of incoming data. In this project, we apply three n- gram based techniques to the problem of HTTP attack detection. The goal of such techniques is to provide a first line of defense by filtering out the vast majority of benign HTTP traffic. We analyze our techniques in terms of accuracy of attack detection and performance. We show …

Automated Rtl Generator, Rohit Kulkarni

Master's Projects

Code generation is a vast topic and has been discussed and implemented for quite a while now. It has been also been a topic of debate as to what is an ideal code generator and how an ideal code generator can be created. The biggest challenge while creating a code generator is to maintain a balance between the amount of freedom given to the user and the restrictions imposed on the code generated. These two seemed to be very conflicting requirements while designing the Automated RTL Code Generator. If the code generator tries to be rigid and sticks to well-defined …

Mongodb Performance In The Cloud, Tudor Matei

Master's Projects

Web applications are growing at a staggering rate every day. As web applications keep getting more complex, their data storage requirements tend to grow exponentially. Databases play an important role in the way web applications store their information. Mongodb is a document store database that does not have strict schemas that RDBMs require and can grow horizontally without performance degradation. MongoDB brings possibilities for different storage scenarios and allow the programmers to use the database as a storage that fits their needs, not the other way around. Scaling MongoDB horizontally requires tens to hundreds of servers, making it very difficult …

Using Social Networks For Assessing Company Sales And Marketing Programs, Vance Tomchalk

Master's Projects

During the course of an extended sales period for a company’s given product line, there are many events that affect the success of its sales. Some of these events include economic downturns, unforeseen shortages and delays that effect the supply chain for the product, and product quality issues that change the perception of the product as a safe and cost-effective choice. In many instances, these events can be tracked by analyzing the signals and messaging present in the social networking media. This analysis requires careful consideration, which the metrics provided by software tools and algorithms lend considerable aid.

Computer-Supported Collaborative Learning: A Research Framework, Yuan Long, Fiona Fui-Hoon Nah, Brenda Eschenbrenner, Terrance Schoonover

Research Collection School Of Computing and Information Systems

Purpose - The purpose of this paper is to propose a computer-supported collaborative learning (CSCL) research framework. Design/methodology/approach - The framework was developed from a review and synthesis of the literature. More specifically, gaps in the literature were identified and a general framework for future CSCL research was proposed. Findings - This paper proposes a research framework that identifies a fit profile between learning objectives, learning tasks, and technology in CSCL. The fit profile, in turn, is expected to influence users' learning processes and outcomes. Research limitations/ implications - This framework can serve as a foundation for future research in …

Delayed Insertion And Rule Effect Moderation Of Domain Knowledge For Reinforcement Learning, Teck-Hou Teng, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

Though not a fundamental pre-requisite to efficient machine learning, insertion of domain knowledge into adaptive virtual agent is nonetheless known to improve learning efficiency and reduce model complexity. Conventionally, domain knowledge is inserted prior to learning. Despite being effective, such approach may not always be feasible. Firstly, the effect of domain knowledge is assumed and can be inaccurate. Also, domain knowledge may not be available prior to learning. In addition, the insertion of domain knowledge can frame learning and hamper the discovery of more effective knowledge. Therefore, this work advances the use of domain knowledge by proposing to delay the …

Volume 05, Ian Karamarkovich, Jessica Cox, Kyle Fowlkes, Allison Pawlowski, Kaitlin Major, Carrie Dunham, Kelsey Scheitlin, Kathryn Grayson, Ashley Johnson, Jennifer Nehrt, Kelsey Stolzenbach, Kristin Mcquarrie, Sara Nelson, Melisa Michelle, Jessica Sudlow, Perry Bason, Danielle Dmuchawski, Mariah Asbell, Matthew Sakach, Timothy Smith Jr., Annaliese Troxell, T. Dane Summerell, Sarah Ganrude, Malina Rutherford, Hannah Hopper, John Berry Jr., James Early, Colleen Festa, Chelsea D. Taylor, Michelle Maddox, Kaitlyn Smith, Sarah Schu, Cabell Edmunds, Katherine Grayson, Kayla Tornai

Incite: The Journal of Undergraduate Scholarship

Introduction from Dean Dr. Charles Ross

The Tallis House as an Extension of Emily Tallis in McEwan's Atonement by Ian Karamarkovich

Graphic Design by Jessica Cox

Graphic Design by Kyle Fowlkes

Graphic Design by Allison Pawlowski

Incorporating Original Research in The Classroom: A Case Study Analyzing the Influence of the Chesapeake Bay on Local Temperatures by Kaitlin Major, Carrie Dunham and Dr. Kelsey Scheitlin

Graphic Design by Kathryn Grayson

Graphic Design by Ashley Johnson

Facing the Music: Environmental Impact Assessment of Building A Concert Hall on North Campus by Jennifer Nehrt, Kelsey Stolzenbach And Dr. Kelsey Scheitlin

Art by Kristin …

Twicube: A Real-Time Twitter Online Community Analysis Tool, Juan Du, Wei Xie, Cheng Li, Feida Zhu, Ee Peng Lim

Research Collection School Of Computing and Information Systems

As a micro-blogging service, Twitter differs from other social network services in two ways: 1) the absence of mutual consent in establishing follow links and 2) being a mixture of news media and social network. A key question to ask in better understanding Twitter user behavior is which part of a user’s Twitter network reflects one’s real-life social network. TwiCube is an online tool that employs a novel algorithm capable of identifying a user’s real-life social community, which we call the user’s off-line community, purely from examining the link structure among the user’s followers and followees. Based on the identified …

Foretell: Aggregating Distributed, Heterogeneous Information From Diverse Sources Using Market-Based Techniques, Janyl Jumadinova

Student Work

Predicting the outcome of uncertain events that will happen in the future is a frequently indulged task by humans while making critical decisions. The process underlying this prediction and decision making is called information aggregation, which deals with collating the opinions of different people, over time, about the future event’s possible outcome. The information aggregation problem is non-trivial as the information related to future events is distributed spatially and temporally, the information gets changed dynamically as related events happen, and, finally, people’s opinions about events’ outcomes depends on the information they have access to and the mechanism they use to …

Towards Omnidirectional Passive Human Detection, Zimu Zhou, Zheng Yang, Chenshu Wu, Longfei Shangguan, Yunhao Liu

Research Collection School Of Computing and Information Systems

Passive human detection and localization serve as key enablers for various pervasive applications such as smart space, human-computer interaction and asset security. The primary concern in devising scenario-tailored detecting systems is the coverage of their monitoring units. In conventional radio-based schemes, the basic unit tends to demonstrate a directional coverage, even if the underlying devices are all equipped with omnidirectional antennas. Such an inconsistency stems from the link-centric architecture, creating an anisotropic wireless propagating environment. To achieve an omnidirectional coverage while retaining the link-centric architecture, we propose the concept of Omnidirectional Passive Human Detection, and investigate to harness the PHY …

Information Security As A Credence Good, Ping Fan Ke, Kai-Lung Hui, Wei Thoo Yue

Research Collection School Of Computing and Information Systems

With increasing use of information systems, many organizations are outsourcing information security protection to a managed security service provider (MSSP). However, diagnosing the risk of an information system requires special expertise, which could be costly and difficult to acquire. The MSSP may exploit their professional advantage and provide fraudulent diagnosis of clients’ vulnerabilities. Such an incentive to mis-represent clients’ risks is often called the credence goods problem in the economics literature[3]. Although different mechanisms have been introduced to tackle the credence goods problem, in the information security outsourcing context, such mechanisms may not work well with the presence of system …

Motion Learning With Biomechanics Principles, Jing Sun

Master's Projects

This project gets the advantage of both biomechanics analysis and Kinect motion capturing, and develops a sports improvement solution with coaching evaluation. It focuses on sample movement patterns to do data quantity and quality analysis. And by combining with professional dedicated bio-mechanical principles, it is able to implement real time motion tracking, coaching and evaluation while motion capturing. We calculate some basic but important parameters from captured motion data, such as the rotation and translation of body segments, and then analyze motion flaws that hid behind it. So a deterministic model for specific movement pattern can be constructed as a …

Beta Atomic Contacts: Identifying Critical Specific Contacts In Protein Binding Interfaces, Qian Lu, Chee Keong Kwoh, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

Specific binding between proteins plays a crucial role in molecular functions and biological processes. Protein binding interfaces and their atomic contacts are typically defined by simple criteria, such as distance-based definitions that only use some threshold of spatial distance in previous studies. These definitions neglect the nearby atomic organization of contact atoms, and thus detect predominant contacts which are interrupted by other atoms. It is questionable whether such kinds of interrupted contacts are as important as other contacts in protein binding. To tackle this challenge, we propose a new definition called beta (β) atomic contacts. Our definition, founded on the …

Modeling Social Information Learning Among Taxi Drivers, Siyuan Liu, Ramayya Krishnan, Emma Brunskill, Lionel Ni

Research Collection School Of Computing and Information Systems

When a taxi driver of an unoccupied taxi is seeking passengers on a road unknown to him or her in a large city, what should the driver do? Alternatives include cruising around the road or waiting for a time period at the roadside in the hopes of finding a passenger or just leaving for another road enroute to a destination he knows (e.g., hotel taxi rank)? This is an interesting problem that arises everyday in many cities worldwide. There could be different answers to the question poised above, but one fundamental problem is how the driver learns about the likelihood …

Roundtriprank: Graph-Based Proximity With Importance And Specificity, Yuan Fang, Kevin Chen-Chuan Chang, Hady W. Lauw

Research Collection School Of Computing and Information Systems

Graph-based proximity has many applications with different ranking needs. However, most previous works only stress the sense of importance by finding "popular” results for a query. Often times important results are overly general without being well-tailored to the query, lacking a sense of specificity— which only emerges recently. Even then, the two senses are treated independently, and only combined empirically. In this paper, we generalize the well-studied importance-based random walk into a round trip and develop RoundTripRank, seamlessly integrating specificity and importance in one coherent process. We also recognize the need for a flexible trade-off between the two senses, and …

Dynamic Label Propagation In Social Networks, Juan Du, Feida Zhu, Ee Peng Lim

Research Collection School Of Computing and Information Systems

Label propagation has been studied for many years, starting from a set of nodes with labels and then propagating to those without labels. In social networks, building complete user profiles like interests and affiliations contributes to the systems like link prediction, personalized feeding, etc. Since the labels for each user are mostly not filled, we often employ some people to label these users. And therefore, the cost of human labeling is high if the data set is large. To reduce the expense, we need to select the optimal data set for labeling, which produces the best propagation result. In this …

Finding The Optimal Social Trust Path For The Selection Of Trustworthy Service Providers In Complex Social Networks, Guanfeng Liu, Yan Wang, Mehmet A. Orgun, Ee Peng Lim

Research Collection School Of Computing and Information Systems

Online social networks have provided the infrastructure for a number of emerging applications in recent years, e.g., for the recommendation of service providers or the recommendation of files as services. In these applications, trust is one of the most important factors in decision making by a service consumer, requiring the evaluation of the trustworthiness of a service provider along the social trust paths from a service consumer to the service provider. However, there are usually many social trust paths between two participants who are unknown to one another. In addition, some social information, such as social relationships between participants and …

Predicting Sql Injection And Cross Site Scripting Vulnerabilities Through Mining Input Sanitization Patterns, Lwin Khin Shar, Hee Beng Kuan Tan

Research Collection School Of Computing and Information Systems

ContextSQL injection (SQLI) and cross site scripting (XSS) are the two most common and serious web application vulnerabilities for the past decade. To mitigate these two security threats, many vulnerability detection approaches based on static and dynamic taint analysis techniques have been proposed. Alternatively, there are also vulnerability prediction approaches based on machine learning techniques, which showed that static code attributes such as code complexity measures are cheap and useful predictors. However, current prediction approaches target general vulnerabilities. And most of these approaches locate vulnerable code only at software component or file levels. Some approaches also involve process attributes that …

Arraytrack: A Fine-Grained Indoor Location System, Jie Xiong, Kyle Jamieson

Research Collection School Of Computing and Information Systems

With myriad augmented reality, social networking, and retail shopping applications all on the horizon for the mobile handheld, a fast and accurate location technology will become key to a rich user experience. When roaming outdoors, users can usually count on a clear GPS signal for accurate location, but indoors, GPS often fades, and so up until recently, mobiles have had to rely mainly on rather coarse-grained signal strength readings. What has changed this status quo is the recent trend of dramatically increasing numbers of antennas at the indoor access point, mainly to bolster capacity and coverage with multiple-input, multiple-output (MIMO) …

Core Versus Peripheral Information Technology Employees And Their Impact On Firm Performance, Ling Liu, Daniel Q. Chen, Nan Hu, Indranil Bose, Garry D. Bruton

Research Collection School Of Computing and Information Systems

Scholars have widely argued, but not previously examined, that core employees with firm specific skills are critical to the firm's strategic success. This argument has led to the belief that employees whose skills are not firm specific can be readily replaced in the external market and are peripheral to the firm's strategic goals. Employing a resource based view of the firm, we find that the core information technology (IT) employees with firm specific skills are value-adding resources that aid the firm's performance whereas peripheral employees with less firm specific skills provide no value to the firm's performance. Examining the issue …