Computer Sciences Commons^™

Computer Systems Design Laboratory, Xiang Meng

Open Educational Resources

No abstract provided.

Computer Organization, Xiang Meng

Open Educational Resources

No abstract provided.

Emerging Non-Volatile Memory Technologies For Computing And Security, Rekha Govindaraj

USF Tampa Graduate Theses and Dissertations

With CMOS technology scaling reaching its limitations rigorous research of alternate and competent technologies is paramount to push the boundaries of computing. Spintronic and resistive memories have proven to be effective alternatives in terms of area, power and performance to CMOS because of their non-volatility, ability for logic computing and easy integration with CMOS. However, deeper investigations to understand their physical phenomenon and improve their properties such as writability, stability, reliability, endurance, uniformity with minimal device-device variations is necessary for deployment as memories in commercial applications. Application of these technologies beyond memory and logic are investigated in this thesis i.e. …

A Neural Network Model For Classifying Bubble-Based Instructor Evaluations, And An Accompanying Web Portal, Jason Held

Graduate Masters Theses

We propose a neural network model for classifying bubbles (circles) used in instructor course evaluations. The model is trained on prior (labeled) objects consisting of bubbles and general text. The trained model is then used to determine the positions of bubble answer options on a given evaluation form. A Web portal accompanies the classification system and facilitates management of the network and analysis of the results. The departmental staff will upload an unevaluated form per course and the system will execute the neural network model on it; application logic will be responsible for ensuring data persistence of the bubble positions …

Hypoxic And Viral Contributions To The Etiopathogenesis Of Schizophrenia: A Whole Transcriptome Analysis, Kathryn A. Gorski

Theses

Schizophrenia is a mental illness with a complex and as of yet unclear etiology. It is highly heritable and has a strong polygenic character, however, studies examining the genetics of schizophrenia have not sufficiently explained all variability in its prevalence. Environmental causes are theorized to have a non trivial contribution to the pathoetiology of schizophrenia, including interactions with genetic components, but these mechanisms remain unclear. Analyzing schizophrenia dysfunction using transcriptomic approaches is a paradigm still in its infancy, and fewer studies still have examined non neurological contributions to schizophrenia pathology with next generation sequencing technologies. This pilot study uses several …

Detecting And Characterizing Self Hiding Behavior In Android Applications, Raina Samuel

Theses

Applications (apps) that conceal their activities are fundamentally deceptive; app marketplaces and end-users should treat such apps as suspicious. However, due to its nature and intent, activity concealing is not disclosed up-front, which puts users at risk. This study focuses on characterization and detection of such techniques, e.g., hiding the app or removing traces, known as 'self hiding' (SH) behavior. SH behavior has not been studied per se - rather it has been reported on only as a byproduct of malware investigations. This gap is addressed via a study and suite of static analyses targeted at SH in Android apps. …

Poster: Towards Safe Refactoring For Intelligent Parallelization Of Java 8 Streams, Yiming Tang, Raffi Khatchadourian, Mehdi Bagherzadeh, Syed Ahmed

Publications and Research

The Java 8 Stream API sets forth a promising new programming model that incorporates functional-like, MapReduce-style features into a mainstream programming language. However, using streams correctly and efficiently may involve subtle considerations. In this poster, we present our ongoing work and preliminary results towards an automated refactoring approach that assists developers in writing optimal stream code. The approach, based on ordering and typestate analysis, determines when it is safe and advantageous to convert streams to parallel and optimize a parallel streams.

Recta: Regulon Identification Based On Comparative Genomics And Transcriptomics Analysis, Xin Chen, Anjun Ma, Adam Mcdermaid, Hanyuan Zhang, Chao Liu, Huansheng Cao, Qin Ma

School of Computing: Faculty Publications

Regulons, which serve as co-regulated gene groups contributing to the transcriptional regulation of microbial genomes, have the potential to aid in understanding of underlying regulatory mechanisms. In this study, we designed a novel computational pipeline, regulon identification based on comparative genomics and transcriptomics analysis (RECTA), for regulon prediction related to the gene regulatory network under certain conditions. To demonstrate the effectiveness of this tool, we implemented RECTA on Lactococcus lactis MG1363 data to elucidate acid-response regulons. A total of 51 regulons were identified, 14 of which have computational-verified significance. Among these 14 regulons, five of them were computationally predicted to …

Sensing Building Structure Using Uwb Radios For Disaster Recovery, Jeong Eun Lee

Dissertations and Theses

This thesis studies the problem of estimating the interior structure of a collapsed building using embedded Ultra-Wideband (UWB) radios as sensors. The two major sensing problems needed to build the mapping system are determining wall type and wall orientation. We develop sensing algorithms that determine (1) load-bearing wall composition, thickness, and location and (2) wall position within the indoor cavity. We use extensive experimentation and measurement to develop those algorithms.

In order to identify wall types and locations, our research approach uses Received Signal Strength (RSS) measurement between pairs of UWB radios. We create an extensive database of UWB signal …

Contents, Adfsl

Annual ADFSL Conference on Digital Forensics, Security and Law

No abstract provided.

Front Matter, Adfsl

Annual ADFSL Conference on Digital Forensics, Security and Law

No abstract provided.

Animal Detection Using R-Cnn

Symposium of Student Scholars

By applying regions on CNN features, R-CNN provides computer vision solutions for multiple-object detection. In our research, we are utilizing AlexNet’s pre-trained model in the Caffe framework to detect approximately 400 different animal species and are acclimating this work from KSU’s GPU server to the Android environment. After an individual downloads the application and an animal is detected, he/she can click on the animal, which will prompt Google to search the animal label. Essentially, this app will allow users to photograph unfamiliar (or familiar) animals for identification and better personal understanding.

Semantic Data Storage In Information Systems, Jean Vincent Fonou Dombeu, Raoul Kwuimi

The African Journal of Information Systems

The storage and retrieval of information are important functions of information systems (IS). These IS functions have been realized for decades, due to the maturity of the relational database technology. In recent years, the concept of Semantic Information System (SIS) has emerged as IS in which information is represented with explicit semantic based on its meaning rather than its syntax to enable its automatic and intelligent processing by computers. At present, there is a shortage of discussions on the topic of semantic data storage in IS as compared to the relational database storage counterpart. This study uses a combination of …

An Adapted Framework For Environmental Sustainability Reporting Using Mobile Technologies, Andre P. Calitz, Jaco F. Zietsman

The African Journal of Information Systems

Corporate governance is the process by which organisations are directed and controlled. King IV is regarded as the cornerstone of corporate governance for businesses and emphasises the importance of sustainability reporting in South Africa. Sustainability reporting guidelines inform organisations how to disclose their most critical affects on the environment, society and the economy. The Global Reporting Initiative (GRI) G4 sustainability reporting framework recommends the Standard Disclosures that all organisations should use to report their sustainability impacts and performance. Sustainability reporting frameworks proposed for the Higher Education sector require reporting principles specific to the needs of Higher Education Institutions (HEIs). The …

Co-Training Of Audio And Video Representations From Self-Supervised Temporal Synchronization, Bruno Korbar

Dartmouth College Undergraduate Theses

There is a natural correlation between the visual and auditive elements of a video. In this work, we use this correlation in order to learn strong and general features via cross-modal self-supervision with carefully chosen neural network architectures and calibrated curriculum learning. We suggest that this type of training is an effective way of pretraining models for further pursuits in video understanding, as they achieve on average 14.8% improvement over models trained from scratch. Furthermore, we demonstrate that these general features can be used for audio classification and perform on par with state-of-the-art results. Lastly, our work shows that using …

An Algorithm For Calculating Top-Dimensional Bounding Chains, J. Frederico Carvalho​, Mikael Vejdemo-Johansson, Danica Kragic, Florian T. Pokorny

Publications and Research

We describe the Coefficient-Flow algorithm for calculating the bounding chain of an (n-1)-boundary on an n-manifold-like simplicial complex S. We prove its correctness and show that it has a computational time complexity of O(|S(n−1)|) (where S(n−1) is the set of (n-1)-faces of S). We estimate the big-O coefficient which depends on the dimension of S and the implementation. We present an implementation, experimentally evaluate the complexity of our algorithm, and compare its performance with that of solving the underlying linear system.

Narrowing The Scope Of Failure Prediction Using Targeted Fault Load Injection, Paul L. Jordan, Gilbert L. Peterson, Alan C. Lin, Michael J. Mendenhall, Andrew J. Sellers

Faculty Publications

As society becomes more dependent upon computer systems to perform increasingly critical tasks, ensuring that those systems do not fail becomes increasingly important. Many organizations depend heavily on desktop computers for day-to-day operations. Unfortunately, the software that runs on these computers is written by humans and, as such, is still subject to human error and consequent failure. A natural solution is to use statistical machine learning to predict failure. However, since failure is still a relatively rare event, obtaining labelled training data to train these models is not a trivial task. This work presents new simulated fault-inducing loads that extend …

Combinatorial Proofs Of Identities Of Alzer And Prodinger And Some Generalizations, John Engbers, Christopher Stocker

Mathematics, Statistics and Computer Science Faculty Research and Publications

We provide combinatorial proofs of identities published by Alzer and Prodinger. These identities include that for integers b, n, and r with b ≥ 1 and n − 1 ≥ r ≥ 0 we have

and for integers b, n, and r with b ≥ 0 and n − 1 ≥ r ≥ 0 we have

Our combinatorial proofs generalize squares to sth powers, and involve generalized Eulerian numbers and generalized Delannoy numbers.

Dynamic Statistical Models For Pyroclastic Density Current Generation At Soufrière Hills Volcano, Robert L. Wolpert, Elaine T. Spiller, Eliza S. Calder

Mathematics, Statistics and Computer Science Faculty Research and Publications

To mitigate volcanic hazards from pyroclastic density currents, volcanologists generate hazard maps that provide long-term forecasts of areas of potential impact. Several recent efforts in the field develop new statistical methods for application of flow models to generate fully probabilistic hazard maps that both account for, and quantify, uncertainty. However, a limitation to the use of most statistical hazard models, and a key source of uncertainty within them, is the time-averaged nature of the datasets by which the volcanic activity is statistically characterized. Where the level, or directionality, of volcanic activity frequently changes, e.g., during protracted eruptive episodes, or at …

An Investigation Into The Effects Of Multiple Kernel Combinations On Solutions Spaces In Support Vector Machines, Paul Kelly, Luca Longo

Conference papers

The use of Multiple Kernel Learning (MKL) for Support Vector Machines (SVM) in Machine Learning tasks is a growing field of study. MKL kernels expand on traditional base kernels that are used to improve performance on non-linearly separable datasets. Multiple kernels use combinations of those base kernels to develop novel kernel shapes that allow for more diversity in the generated solution spaces. Customising these kernels to the dataset is still mostly a process of trial and error. Guidelines around what combinations to implement are lacking and usually they requires domain specific knowledge and understanding of the data. Through a brute …

Towards Mitigating Co-Incident Peak Power Consumption And Managing Energy Utilization In Heterogeneous Clusters, Renan Delvalle Rueda

Graduate Dissertations and Theses

As data centers continue to grow in scale, the resource management software needs to work closely with the hardware infrastructure to provide high utilization, performance, fault tolerance, and high availability. Apache Mesos has emerged as a leader in this space, providing an abstraction over the entire cluster, data center, or cloud to present a uniform view of all the resources. In addition, frameworks built on Mesos such as Apache Aurora, developed within Twitter and later contributed to the Apache Software Foundation, allow massive job submissions with heterogeneous resource requirements. The availability of such tools in the Open Source space, with …

An Analysis Of Frenkel Defects And Backgrounds Modeling For Supercdms Dark Matter Searches, Matthew Stein

Physics Theses and Dissertations

Years of astrophysical observations suggest that dark matter comprises more than ~80 % of all matter in the universe. Particle physics theories favor a weakly-interacting particle that could be directly detected in terrestrial experiments. The Super Cryogenic Dark Matter Search (SuperCDMS) Collaboration operates world-leading experiments to directly detect dark matter interacting with ordinary matter. The SuperCDMS Soudan experiment searched for weakly interacting massive particles (WIMPs) via their elastic-scattering interactions with nuclei in low-temperature germanium detectors.

During the operation of the SuperCDMS Soudan experiment, ²¹⁰Pb sources were installed to study background rejection of the Ge detectors. Data from these sources …

A Survey Of Lawyers’ Cyber Security Practises In Western Australia, Craig Valli, Mike Johnstone, Rochelle Fleming

Annual ADFSL Conference on Digital Forensics, Security and Law

This paper reports on the results of a survey that is the initial phase of an action research project being conducted with the Law Society of Western Australia. The online survey forms a baseline for the expression of a targeted training regime aimed at improving the cyber security awareness and posture of the membership of the Society. The full complement of over 3000 members were given the opportunity to participate in the survey, with 122 members responding in this initial round. The survey was designed to elicit responses about information technology use and the awareness of good practices with respect …

Analysis Of Data Erasure Capability On Sshd Drives For Data Recovery, Andrew Blyth

Annual ADFSL Conference on Digital Forensics, Security and Law

Data Protection and Computer Forensics/Anti-Forensics has now become a critical area of concern for organizations. A key element to this is how data is sanitized at end of life. In this paper we explore Hybrid Solid State Hybrid Drives (SSHD) and the impact that various Computer Forensics and Data Recovery techniques have when performing data erasure upon a SSHD.

Knowledge Expiration In Security Awareness Training, Tianjian Zhang

Annual ADFSL Conference on Digital Forensics, Security and Law

No abstract provided.

Positive Identification Of Lsb Image Steganography Using Cover Image Comparisons, Michael Pelosi, Nimesh Poudel, Pratap Lamichhane, Devon Lam, Gary Kessler, Joshua Macmonagle

Annual ADFSL Conference on Digital Forensics, Security and Law

In this paper we introduce a new software concept specifically designed to allow the digital forensics professional to clearly identify and attribute instances of LSB image steganography by using the original cover image in side-by-side comparison with a suspected steganographic payload image. The “CounterSteg” software allows detailed analysis and comparison of both the original cover image and any modified image, using sophisticated bit- and color-channel visual depiction graphics. In certain cases, the steganographic software used for message transmission can be identified by the forensic analysis of LSB and other changes in the payload image. The paper demonstrates usage and typical …

Exploring The Use Of Graph Databases To Catalog Artifacts For Client Forensics, Rose Shumba

Annual ADFSL Conference on Digital Forensics, Security and Law

Cloud computing has revolutionized the methods by which digital data is stored, processed, and transmitted. It is providing users with data storage and processing services, enabling access to resources through multiple devices. Although organizations continue to embrace the advantages of flexibility and scalability offered by cloud computing, insider threats are becoming a serious concern as cited by security researchers. Insiders can use authorized access to steal sensitive information, calling for the need for an investigation. This concept paper describes research in progress towards developing a Neo4j graph database tool to enhance client forensics. The tool, with a Python interface, allows …

Appendix: A Reasonable Bias Approach To Gerrymandering: Using Automated Plan Generation To Evaluate Redistricting Proposals, Bruce E. Cain, Wendy K. Tam Cho, Yan Y. Liu, Emily R. Zhang

William & Mary Law Review Online

Here, we present our findings, analogous to those on the efficiency gap in Part I.B of our Article published in the print edition of the William & Mary Law Review, on the other measures of partisan fairness.

Detecting Rip Currents From Images, Corey C. Maryan

LSU New Orleans Theses and Dissertations

Rip current images are useful for assisting in climate studies but time consuming to manually annotate by hand over thousands of images. Object detection is a possible solution for automatic annotation because of its success and popularity in identifying regions of interest in images, such as human faces. Similarly to faces, rip currents have distinct features that set them apart from other areas of an image, such as more generic patterns of the surf zone. There are many distinct methods of object detection applied in face detection research. In this thesis, the best fit for a rip current object detector …

A Jython-Based Restful Web Service Api For Python Code Reflection, John A. Nielson

LSU New Orleans Theses and Dissertations

Often times groups of domain experts, such as scientists and engineers, will develop their own software modules for specialized computational tasks. When these users determine there is a need to integrate the data and computations used in their specialized components with an enterprise data management system, interoperability between the enterprise system and the specialized components rather than re-implementation allows for faster implementation and more flexible change management by shifting the onus of changes to the scientific components to the subject matter experts rather than the enterprise information technology team. The Jython-based RESTful web service API was developed to leverage code …