Computer Sciences Commons^™

Physical Activity In A Theory Of Computing Class, Nancy Lynn Tinkham

ACMS Conference Proceedings 2015

Physical activity breaks, sometimes called brain breaks, are beginning to gain attention among K-12 teachers as a way to keep their students alert and engaged in the classroom. In the Fall 2014 semester, faced with the task of teaching an introductory course in Theory of Computing in a once-a-week, 2 1/2-hour format, I decided to try incorporating physical activity into my own classroom. Time is precious in the college classroom, so any physical activities have to be directly related to the course material. I will describe some physically active exercises that I used in the classroom to teach students about …

Preparing Students To Read A Calculus Textbook, Douglas Phillippy

ACMS Conference Proceedings 2015

Consider the exercise of reading the textbook before class. While most educators agree that this practice leads to better learning, too often students enrolled in a calculus class do not find pre-class reading a valuable use of their time, and their commitment to doing so fades. Why is this? As instructors, we hope that these students will be well-versed in the fundamental concepts of the subject by the time they prepare for their final exam, but as they progress through the course and encounter new concepts, they may not be ready for the technical language of the standard calculus textbook. …

Pressure And Impulse In Student Learning: What I Learned From Teaching Physics, Kim Jongerius

ACMS Conference Proceedings 2015

In the fall of 2014, a one-semester gap between the departure of one physics professor and the arrival of the next afforded me the opportunity(?) to teach a first-semester, calculus-based physics class. The thirty-year gap between the last (of three) physics courses I had taken myself and this course I was to teach, combined with a two-week notice prior to the start of the semester, placed me in the interesting position of learning alongside my students. Wading through an unfamiliar text, trying to understand publisher-produced lecture slides, learning from and getting frustrated with online homework, entering review sessions fearful of …

Paper Abstracts (2015), Association Of Christians In The Mathematical Sciences

ACMS Conference Proceedings 2015

Twentieth Conference of the Association of Christians in the Mathematical Sciences

Introduction (2015), Thomas Price, Derek Schuurman, Kevin Vander Meulen

ACMS Conference Proceedings 2015

Twentieth Conference of the Association of Christians in the Mathematical Sciences

Table Of Contents (2015), Association Of Christians In The Mathematical Sciences

ACMS Conference Proceedings 2015

Twentieth Conference of the Association of Christians in the Mathematical Sciences

Why Do Protein Structures Recur?, Rebecca G. Leong

Dartmouth College Undergraduate Theses

Protein tertiary structures exhibit an observable degeneracy in nature. This paper examines the connection between a protein motif's abundance in nature and its designability as measured by in silico methods. After generating a set of protein structures, we evaluated each structure's abundance in nature, ratio of possible contacts (contact degree) and in silico designability. Our results showed that any two or these metrics are moderately correlated. Together abundance and contact degree produced the strongest correlation with in silico designability. Our results suggest that abundance is indeed an indicator of designability. Furthermore, abundance and contact degree appear to correlate with some …

Mining Concept In Big Data, Jingjing Yang

Master's Projects

To fruitful using big data, data mining is necessary. There are two well-known methods, one is based on apriori principle, and the other one is based on FP-tree. In this project we explore a new approach that is based on simplicial complex, which is a combinatorial form of polyhedron used in algebraic topology. Our approach, similar to FP-tree, is top down, at the same time, it is based on apriori principle in geometric form, called closed condition in simplicial complex. Our method is almost 300 times faster than FP-growth on a real world database using a SJSU laptop. The database …

Proceedings Of The Twentieth Conference Of The Association Of Christians In The Mathematical Sciences, Association Of Christians In The Mathematical Sciences

ACMS Conference Proceedings 2015

The proceedings of the twentieth conference of the Associate of Christians in the Mathematical Sciences held at Redeemer University College from May 27-30, 2015.

Low-Rank Based Algorithms For Rectification, Repetition Detection And De-Noising In Urban Images, Juan Liu

Dissertations, Theses, and Capstone Projects

In this thesis, we aim to solve the problem of automatic image rectification and repeated patterns detection on 2D urban images, using novel low-rank based techniques. Repeated patterns (such as windows, tiles, balconies and doors) are prominent and significant features in urban scenes.

Detection of the periodic structures is useful in many applications such as photorealistic 3D reconstruction, 2D-to-3D alignment, facade parsing, city modeling, classification, navigation, visualization in 3D map environments, shape completion, cinematography and 3D games. However both of the image rectification and repeated patterns detection problems are challenging due to scene occlusions, varying illumination, pose variation and sensor …

Theory And Applications Of Outsider Anonymity In Broadcast Encryption, Irippuge Deshan Milinda Perera

Dissertations, Theses, and Capstone Projects

Broadcast Encryption (BE) allows efficient one-to-many secret communication of data over a broadcast channel. In the standard setting of BE, information about receivers is transmitted in the clear together with ciphertexts. This could be a serious violation of recipient privacy since the identities of the users authorized to access the secret content in certain broadcast scenarios are as sensitive as the content itself. Anonymous Broadcast Encryption (AnoBe) prevents this leakage of recipient identities from ciphertexts but at a cost of a linear lower bound (in the number of receivers) on the length of ciphertexts. A linear ciphertext length is a …

Methods And Systems For Biclustering Algorithm, Donald C. Wunsch, Rui Xu, Sejun Kim

Electrical and Computer Engineering Faculty Research & Creative Works

Methods and systems for improved unsupervised learning are described. The unsupervised learning can consist of biclustering a data set, e.g., by biclustering subsets of the entire data set. In an example, the biclustering does not include feeding know and proven results into the biclustering methodology or system. A hierarchical approach can be used that feeds proven clusters back into the biclustering methodology or system as the input. Data that does not cluster may be discarded. Thus, a very large unknown data set can be acted on to learn about the data. The system is also amenable to parallelization.

A Neuronal Classification System For Plant Leaves Using Genetic Image Segmentation, Oluleye Babatunde, Leisa Armstrong, Dean Diepeveen, Jinsong Leng

Grain and Other Field Crops Research Articles

This paper demonstrates the use of radial basis networks (RBF), cellular neural networks (CNN)and genetic algorithm (GA) for automatic classification of plant leaves. A genetic neuronal system herein attempted to solve some of the inherent challenges facing current software being employed for plant leaf classification. The image segmentation module in this work was genetically optimized to bring salient features in the images of plants leaves used in this work. The combination of GA-based CNN with RBF in this work proved more efficient than the existing systems that use conventional edge operators such as Canny, LoG, Prewitt, and Sobel operators. The …

Introducing Faceted Exception Handling For Dynamic Information Flow, Sri Tej Narala

Master's Projects

JavaScript is most commonly used as a part of web browsers, especially client- side scripts interacting with the user. JavaScript is also the source of many security problems, which includes cross-site scripting attacks. The primary challenge is that code from untrusted sources run with full privileges on the client side, thus lead- ing to security breaches. This paper develops information flow controls with proper exception handling to prevent violations of data confidentiality and integrity.

Faceted values are a mechanism to handle dynamic information flow security in a way that overcomes the limitations caused by dynamic execution, but previous work has …

Support Vector Machines And Metamorphic Malware Detection, Tanuvir Singh

Master's Projects

Metamorphic malware changes its internal structure with each infection, which makes it challenging to detect. In this research, we test several scor- ing techniques that have shown promise in metamorphic detection. We then perform a careful robustness analysis by employing morphing strategies that cause each score to fail. Finally, we show that combining scores using a Sup- port Vector Machine (SVM) yields results that are significantly more robust than we obtained using any of the individual scores.

Adding Syntax Parameters To The Sweet.Js Macro Library For Javascript, Vimal Kumar

Master's Projects

Lisp and Scheme have demonstrated the power of macros to enable programmers to evolve and craft languages. A macro is a rule or pattern that specifies how a certain input sequence should be mapped to an output sequence according to some defined procedure. Using a macro system a programmer can introduce new syntactic elements to the programming language. Macros found in a program are expanded by a macro expander and allow a programmer to enable code reuse. Mozilla Sweet.JS provides a way for developers to enrich their JavaScript code by adding new syntax to the language through the use of …

Cryptanalysis Of Classic Ciphers Using Hidden Markov Models, Rohit Vobbilisetty

Master's Projects

Cryptanalysis is the study of identifying weaknesses in the implementation of cryptographic algorithms. This process would improve the complexity of such algo- rithms, making the system secure.

In this research, we apply Hidden Markov Models (HMMs) to classic cryptanaly- sis problems. We show that with sufficient ciphertext, an HMM can be used to break a simple substitution cipher. We also show that when limited ciphertext is avail- able, using multiple random restarts for the HMM increases our chance of successful decryption.

Malware Detection Using Dynamic Analysis, Swapna Vemparala

Master's Projects

In this research, we explore the field of dynamic analysis which has shown promis- ing results in the field of malware detection. Here, we extract dynamic software birth- marks during malware execution and apply machine learning based detection tech- niques to the resulting feature set. Specifically, we consider Hidden Markov Models and Profile Hidden Markov Models. To determine the effectiveness of this dynamic analysis approach, we compare our detection results to the results obtained by using static analysis. We show that in some cases, significantly stronger results can be obtained using our dynamic approach.

A Comparison Of Clustering Techniques For Malware Analysis, Swathi Pai

Master's Projects

In this research, we apply clustering techniques to the malware detection problem. Our goal is to classify malware as part of a fully automated detection strategy. We compute clusters using the well-known �-means and EM clustering algorithms, with scores obtained from Hidden Markov Models (HMM). The previous work in this area consists of using HMM and �-means clustering technique to achieve the same. The current effort aims to extend it to use EM clustering technique for detection and also compare this technique with the �-means clustering.

Clustering Versus Svm For Malware Detection, Usha Narra

Master's Projects

Previous work has shown that we can effectively cluster certain classes of mal- ware into their respective families. In this research, we extend this previous work to the problem of developing an automated malware detection system. We first compute clusters for a collection of malware families. Then we analyze the effectiveness of clas- sifying new samples based on these existing clusters. We compare results obtained using �-means and Expectation Maximization (EM) clustering to those obtained us- ing Support Vector Machines (SVM). Using clustering, we are able to detect some malware families with an accuracy comparable to that of SVMs. One …

Optimization Of Scheduling And Dispatching Cars On Demand, Vu Tran

Master's Projects

Taxicab is the most common type of on-demand transportation service in the city because its dispatching system offers better services in terms of shorter wait time. However, the shorter wait time and travel time for multiple passengers and destinations are very considerable. There are recent companies implemented the real-time ridesharing model that expects to reduce the riding cost when passengers are willing to share their rides with the others. This model does not solve the shorter wait time and travel time when there are multiple passengers and destinations. This paper investigates how the ridesharing can be improved by using the …

Firefox Add-On For Metamorphic Javascript Malware Detection, Sravan Kumar Reddy Javaji

Master's Projects

With the increasing use of the Internet, malicious software has more frequently been designed to take control of users computers for illicit purposes. Cybercriminals are putting a lot of efforts to make malware difficult to detect. In this study, we demonstrate how the metamorphic JavaScript malware can effect a victim’s machine using a malicious or compromised Firefox add-on. Following the same methodology, we develop another add-on with malware static detection technique to detect metamorphic JavaScript malware.

Tracking Criminals On Facebook: A Case Study From A Digital Forensics Reu Program, Daniel Weiss, Gary Warner

Annual ADFSL Conference on Digital Forensics, Security and Law

The 2014 Digital Forensics Research Experience for Undergraduates (REU) Program at the University of Alabama at Birmingham (UAB) focused its summer efforts on tracking criminal forums and Facebook groups. The UAB-REU Facebook team was provided with a list of about 60 known criminal groups on Facebook, with a goal to track illegal information posted in these groups and ultimately store the information in a searchable database for use by digital forensic analysts. Over the course of about eight weeks, the UAB-REU Facebook team created a database with over 400 Facebook groups conducting criminal activity along with over 100,000 unique users …

Towards A Digital Forensics Competency-Based Program: Making Assessment Count, Rose Shumba

Annual ADFSL Conference on Digital Forensics, Security and Law

This paper describes an approach that UMUC has initiated to revise its graduate programs to a Competency-Based Education (CBE) curriculum. The approach, which is Learning Demonstration (LD) centric, includes the identification of learning goals and competences, identification and description of the LDs, mapping of the LDs to the competences, scripting the LDs, placing the LDs into the respective courses, validating the developed materials, and the development of the open learning resources. Programs in the Cybersecurity and Information Assurance Department, including the Digital Forensics and Cyber Investigations program, are being revised. An LD centric approach to curriculum development helps align programs …

Phishing Intelligence Using The Simple Set Comparison Tool, Jason Britt, Alan Sprague, Gary Warner

Annual ADFSL Conference on Digital Forensics, Security and Law

Phishing websites, phish, attempt to deceive users into exposing their passwords, user IDs, and other sensitive information by imitating legitimate websites, such as banks, product vendors, and service providers. Phishing investigators need fast automated tools to analyze the volume of phishing attacks seen today. In this paper, we present the Simple Set Comparison tool. The Simple Set Comparison tool is a fast automated tool that groups phish by imitated brand allowing phishing investigators to quickly identify and focus on phish targeting a particular brand. The Simple Set Comparison tool is evaluated against a traditional clustering algorithm over a month's worth …

Identifying Common Characteristics Of Malicious Insiders, Nan Liang, David Biros

Annual ADFSL Conference on Digital Forensics, Security and Law

Malicious insiders account for large proportion of security breaches or other kinds of loss for organizations and have drawn attention of both academics and practitioners. Although methods and mechanism have been developed to monitor potential insider via electronic data monitoring, few studies focus on predicting potential malicious insiders. Based on the theory of planned behavior, certain cues should be observed or expressed when an individual performs as a malicious insider. Using text mining to analyze various media content of existing insider cases, we strive to develop a method to identify crucial and common indicators that an individual might be a …

Pinpoint: Efficient And Effective Resource Isolation For Mobile Security And Privacy, Paul Ratazzi, Ashok Bommisetti, Nian Ji, Wenliang Du

Electrical Engineering and Computer Science - All Scholarship

Virtualization is frequently used to isolate untrusted processes and control their access to sensitive resources. However, isolation usually carries a price in terms of less resource sharing and reduced inter-process communication. In an open architecture such as Android, this price and its impact on performance, usability, and transparency must be carefully considered. Although previous efforts in developing general-purpose isolation solutions have shown that some of these negative sideeffects can be mitigated, doing so involves overcoming significant design challenges by incorporating numerous additional platform complexities not directly related to improved security. Thus, the general purpose solutions become inefficient and burdensome if …

Index Strategies For Efficient And Effective Entity Search, Huy T. Vu

Master's Projects

The volume of structured data has rapidly grown in recent years, when data-entity emerged as an abstraction that captures almost every data pieces. As a result, searching for a desired piece of information on the web could be a challenge in term of time and relevancy because the number of matching entities could be very large for a given query. This project concerns with the efficiency and effectiveness of such entity queries. The work contains two major parts: implement inverted indexing strategies so that queries can be searched in minimal time, and rank results based on features that are independent …

Cheating Detection In Online Examinations, Gaurav Kasliwal

Master's Projects

In this research, we develop and analyze a tool that monitor student browsing activity during online examination. Our goal is to detect cheating in real time. In our design, a server capture packets using KISMET and detects cheating based on either a whitelist or blacklist of URLs. We provide implementation details and give experimental results, and we analyze various attack strategies. Finally, we show that the system is practical and lightweight in comparison to other available tools.

An Open Source Advertisement Server, Pushkar Umaranikar

Master's Projects

This report describes a new online advertisement system and its implementation for the Yioop open source search engine. This system was implemented for my CS298 project. It supports both selling advertisements and displaying them within search results. The selling of advertisement is done using a novel auction system, which we describe in this paper. With this auction system, it is possible to create an advertisement, attach keywords to it, and add it to the advertisement inventory. An advertisement is displayed on a search results page if the search keyword matches the keywords attached to the advertisement. Display of advertisements is …